The document describes experiments conducted in MATLAB to visualize and understand various continuous-time and discrete-time signals. In experiment 1, common continuous signals like unit step, ramp, impulse etc. are plotted. Experiment 2 involves plotting corresponding discrete-time signals. The document provides MATLAB code examples to generate and plot these standard signals.
1. The document discusses different types of systems based on their properties, including static vs dynamic, time-variant vs time-invariant, linear vs non-linear, causal vs non-causal, and stable vs unstable.
2. A system is defined as a physical device or algorithm that performs operations on a discrete-time signal. Static systems have outputs that depend only on the present input, while dynamic systems have outputs that depend on present and past/future inputs.
3. Time-invariant systems have characteristics that do not change over time, while time-variant systems have characteristics that do change. Linear systems follow the superposition principle, while causal systems have outputs dependent only on present and past inputs.
Digital electronics(EC8392) unit- 1-Sesha Vidhya S/ ASP/ECE/RMKCETSeshaVidhyaS
Number systems, Number conversion,Logic Gates,Boolean Theorem and Laws,Boolean Simplification,NAND,NOR Implementation,K-MAP simplification and Tabulation Method
This document discusses different types of modulation including amplitude modulation (AM), frequency modulation (FM), phase modulation (PM), and pulse width modulation (PWM). It defines each type of modulation and compares their characteristics. It also discusses the needs for modulation, advantages and disadvantages of PM, and the relationship between PM and FM.
The document discusses transmission line impedance and input impedance. It defines characteristic impedance as the ratio of voltage to current waves travelling along a transmission line. It provides expressions for characteristic impedance in terms of line parameters R, L, G, C. It then derives expressions for input impedance of open circuit, short circuit, matched and mismatched lossless transmission lines. It shows that input impedance is capacitive for a short open circuit line and inductive for a short circuit line.
This document describes a script that simulates bit error rate (BER) performance for BPSK modulation over a Rayleigh fading channel with a 2 transmitter and 2 receiver (2x2) multiple-input multiple-output (MIMO) system using zero forcing equalization. The script generates transmitted bits, applies BPSK modulation, sends the signals over a Rayleigh fading channel with additive noise, uses zero forcing equalization at the receiver, and compares the estimated and transmitted bits to calculate the simulated BER over a range of signal-to-noise ratio (SNR) values. The simulated results are then plotted along with theoretical BER curves for 1x1 and 2x2 MIMO systems.
CT and PT Instrument transformer | basic information with some most asked que...AkhileshDeshmukh5
This ppt contains all basic information about instrument transformer le CT and PT which is explained in baase manner. In this ppt, you will also get to learn about questions which are asked in the interview about CT and PT.
1. The document discusses different types of systems based on their properties, including static vs dynamic, time-variant vs time-invariant, linear vs non-linear, causal vs non-causal, and stable vs unstable.
2. A system is defined as a physical device or algorithm that performs operations on a discrete-time signal. Static systems have outputs that depend only on the present input, while dynamic systems have outputs that depend on present and past/future inputs.
3. Time-invariant systems have characteristics that do not change over time, while time-variant systems have characteristics that do change. Linear systems follow the superposition principle, while causal systems have outputs dependent only on present and past inputs.
Digital electronics(EC8392) unit- 1-Sesha Vidhya S/ ASP/ECE/RMKCETSeshaVidhyaS
Number systems, Number conversion,Logic Gates,Boolean Theorem and Laws,Boolean Simplification,NAND,NOR Implementation,K-MAP simplification and Tabulation Method
This document discusses different types of modulation including amplitude modulation (AM), frequency modulation (FM), phase modulation (PM), and pulse width modulation (PWM). It defines each type of modulation and compares their characteristics. It also discusses the needs for modulation, advantages and disadvantages of PM, and the relationship between PM and FM.
The document discusses transmission line impedance and input impedance. It defines characteristic impedance as the ratio of voltage to current waves travelling along a transmission line. It provides expressions for characteristic impedance in terms of line parameters R, L, G, C. It then derives expressions for input impedance of open circuit, short circuit, matched and mismatched lossless transmission lines. It shows that input impedance is capacitive for a short open circuit line and inductive for a short circuit line.
This document describes a script that simulates bit error rate (BER) performance for BPSK modulation over a Rayleigh fading channel with a 2 transmitter and 2 receiver (2x2) multiple-input multiple-output (MIMO) system using zero forcing equalization. The script generates transmitted bits, applies BPSK modulation, sends the signals over a Rayleigh fading channel with additive noise, uses zero forcing equalization at the receiver, and compares the estimated and transmitted bits to calculate the simulated BER over a range of signal-to-noise ratio (SNR) values. The simulated results are then plotted along with theoretical BER curves for 1x1 and 2x2 MIMO systems.
CT and PT Instrument transformer | basic information with some most asked que...AkhileshDeshmukh5
This ppt contains all basic information about instrument transformer le CT and PT which is explained in baase manner. In this ppt, you will also get to learn about questions which are asked in the interview about CT and PT.
Mathematical model for communication channelssafeerakd
This document discusses mathematical models for communication channels. It begins by showing a block diagram of a basic digital communication system and defines the key components. It then discusses different types of communication channels and mediums that can be used to transmit signals, including wires, wireless spectra, and optical fibers. The rest of the document discusses several common mathematical models used to represent communication channels, including additive noise channels, linear filter channels, and linear time-variant filter channels. It also discusses parameters that characterize channels and limits on data transmission rates. Finally, it covers optimum receivers for signals corrupted by additive white Gaussian noise.
This document summarizes different types of noise in electronic components, including thermal noise, shot noise, flicker noise, antenna noise, and noise figure. It discusses various noise sources such as Johnson noise, atmospheric noise, solar noise, galactic noise, ground noise, and man-made noise. It also covers concepts like equivalent noise temperature, available noise power, noise power spectrum density, and methods for measuring noise temperature including the gain method and Y-factor method.
The document describes an FM receiver project. It includes the group members, an overview of radio receivers and how they work, classifications of receivers, details on AM and FM receivers, the circuit diagram and components of the FM receiver, and descriptions of the main sections in the block diagram including the RF amplifier, mixer, filter, IF amplifier, limiter, demodulator, AF amplifier, and oscillator.
This document discusses sampling and related concepts in signal processing. It begins by introducing the need to convert analog signals to discrete-time signals for digital processing. It then covers the sampling theorem, which states that a band-limited signal can be reconstructed if sampled at twice the maximum frequency. The document describes three main sampling methods: ideal (impulse), natural (pulse), and flat-top sampling. It also discusses aliasing, which occurs when a signal is under-sampled. The key aspects of sampling covered are the sampling rate, reconstruction of sampled signals, and anti-aliasing filters.
The document discusses Boolean expressions and their use in computer programming. It defines Boolean expressions as expressions that evaluate to true or false. Boolean expressions are composed of logical operators like AND, OR, and NOT. The document then discusses different logical operators and their truth tables. It also covers Boolean algebra identities and theorems. Finally, it introduces concepts like minterms, maxterms, sum of products, and product of sums and how Karnaugh maps can be used to simplify Boolean expressions.
This document provides an introduction to signals and systems. It defines a signal as a function that carries information about a physical phenomenon, and a system as an entity that processes signals to produce new outputs. Signals can be classified as continuous or discrete, deterministic or random, periodic or aperiodic, even or odd, energy-based or power-based, and causal or noncausal. The document discusses examples and properties of different signal types and how systems manipulate inputs to generate outputs. It covers key concepts like energy, power, periodicity, causality, and system modeling that are important foundations for signals and systems analysis.
Comparator circuits compare two input voltages and produce a logic output signal that is high or low depending on which input is larger. Real comparators do not have an abrupt transition and have very high voltage gain in the transition region. Comparators are often used as interfaces between analog and digital circuits by converting analog signals to logic levels. Open-collector outputs are useful for this by producing either 0V or the supply voltage at their outputs. Schmitt triggers, which are comparators with positive feedback, are commonly used as they introduce hysteresis which helps eliminate unwanted output transitions from noise.
The document discusses different methods for demodulating DSBSC waves, including coherent detection, Costas loop, and squaring loop. Coherent detection extracts the message signal by multiplying the DSBSC wave with a local oscillator signal that is coherent in frequency and phase with the carrier. Costas loop is used to maintain phase coherence between the local oscillator and carrier. Squaring loop recovers the carrier signal by filtering the output of a squaring circuit to extract the signal at twice the carrier frequency.
Este documento trata sobre diferentes tipos de filtros y ecualizadores utilizados en el procesado de señales de audio. Explica conceptos como filtros paso alto y paso bajo, filtros de control de tono, filtros resonantes y banda eliminada. También describe las tecnologías de implementación de filtros, incluyendo filtros pasivos, activos y digitales, y cómo han evolucionado para lograr un factor de calidad constante.
This document outlines a course on pulse and linear integrated circuits taught at Matrusri Engineering College. The course objectives are to analyze linear and non-linear wave shaping circuits, multivibrators, operational amplifiers, and various data converter circuits. The course is divided into units that will cover linear and non-linear wave shaping, attenuators, clipping circuits, clamping circuits, and applications of operational amplifiers and timers. Students will analyze circuit responses to different input signals and learn to design circuits using transistors and operational amplifiers.
The document discusses various types of meters used to measure voltage and current in DC and AC circuits. It describes DC ammeters, which use shunt resistors to measure higher currents beyond the range of the meter movement. Multi-range ammeters use multiple shunts and a range switch to extend the measurement range. DC voltmeters use a series resistor called a multiplier to limit the current through the meter movement. Multi-range voltmeters similarly use multiple multipliers and a range switch. AC meters rectify the input voltage before measuring to obtain the average value using a DC meter. Instrument transformers like current transformers and potential transformers are used to safely measure high currents and voltages in power systems.
This document discusses tracking in receivers. It describes that tracking is the process where the local oscillator frequency follows the signal frequency to maintain the correct intermediate frequency. It explains two types of tracking: two-point tracking using a padder or trimmer capacitor, and three-point tracking which combines both. The purpose of tracking is to minimize any error between the local oscillator and signal frequencies.
A microphone is a transducer that converts sound waves into electrical signals. The quality of a microphone is determined by its characteristics, including sensitivity, signal-to-noise ratio, frequency response, distortion, directivity, and output impedance. Sensitivity measures how well a microphone detects weak sounds, signal-to-noise ratio compares the signal level to the noise floor, and frequency response specifies the range of frequencies accurately reproduced. Ideal microphones have high sensitivity and signal-to-noise ratio, a flat frequency response across most of the audible range, low distortion, and correct output impedance for the application.
Transmission line, single and double matchingShankar Gangaju
This document discusses different types of transmission lines used for transmitting energy and signals over long distances. It describes common transmission line media like twisted pair, coaxial cable and optical fiber. It covers their applications in telephone networks, buildings and computer networks. It also discusses their transmission characteristics and limitations. The document compares properties of unshielded and shielded twisted pair. It provides details on utilizing different wavelengths in optical fiber for various applications.
Here are the steps to find the cutoff frequency:
1) The voltage gain is 3 dB down from the maximum gain at the cutoff frequency.
2) The maximum gain from Step 2 is 4.006 dB.
3) 4.006 dB - 3 dB = 1.006 dB
4) The point on the curve that is 1.006 dB down is the cutoff frequency.
Record this on the curve:
fc = 1.006 dB
fc = 10 kHz
Question: Is the calculated cutoff frequency (fc) in Step 6 equal to the expected cutoff
frequency based on the circuit component values? Explain.
No, the calculated cutoff frequency (10 kHz) in Step 6 is not
This document discusses the generation of frequency modulation (FM) using direct and indirect methods. The direct method uses a reactance modulator like a varactor diode or FET placed across an LC oscillator tank circuit to vary the capacitance or inductance in proportion to the modulating voltage. The indirect method generates FM through phase modulation using a crystal oscillator and phase modulator, then detecting the phase changes to create FM. Vector diagrams are also presented to illustrate phase modulation. Effects of frequency changing like multiplication and mixing on FM signals are explained.
A power amplifier is an electronic device that increases the power of an input signal so it can drive output devices like speakers or radio transmitters. It amplifies low-power signals to a higher power level needed to power external devices. Power amplifiers are used to boost signals to a level sufficient for driving loads such as speakers or transmitting antennas.
This document discusses resonance in series and parallel RLC circuits. It defines key parameters for both circuit types including resonance frequency, half-power frequencies, bandwidth, and quality factor. The series resonance circuit is analyzed showing that impedance is purely resistive at resonance, with maximum current and unity power factor. Parallel resonance is also examined, with admittance being purely conductance at resonance. Formulas for calculating important resonant characteristics are provided.
The document describes MATLAB software and its uses for signal processing. MATLAB is a matrix-based program for scientific and engineering computation. It provides built-in functions for technical computation, graphics, and animation. The Signal Processing Toolbox contains functions for filtering, Fourier transforms, convolution, and filter design. The document lists some important MATLAB commands and frequently used signal processing functions, along with their syntax and purpose. It also describes the basic windows of the MATLAB interface and provides examples of generating common continuous and discrete time signals using MATLAB code.
This document contains information about the Digital Signal Processing lab at Shadan College of Engineering & Technology. It includes:
1. A list of 12 experiments to be conducted in the lab, related to topics like generating signals, implementing filters, and analyzing system responses.
2. An introduction to MATLAB, describing its basic functions and capabilities for numerical computation and signal processing.
3. Programs and instructions for carrying out specific DSP experiments in MATLAB, including generating basic signals, computing the DFT/IDFT of sequences, and determining the impulse/frequency responses of systems defined by difference equations.
The document provides students with an overview of the lab activities and teaches them how to use MATLAB for digital signal
Mathematical model for communication channelssafeerakd
This document discusses mathematical models for communication channels. It begins by showing a block diagram of a basic digital communication system and defines the key components. It then discusses different types of communication channels and mediums that can be used to transmit signals, including wires, wireless spectra, and optical fibers. The rest of the document discusses several common mathematical models used to represent communication channels, including additive noise channels, linear filter channels, and linear time-variant filter channels. It also discusses parameters that characterize channels and limits on data transmission rates. Finally, it covers optimum receivers for signals corrupted by additive white Gaussian noise.
This document summarizes different types of noise in electronic components, including thermal noise, shot noise, flicker noise, antenna noise, and noise figure. It discusses various noise sources such as Johnson noise, atmospheric noise, solar noise, galactic noise, ground noise, and man-made noise. It also covers concepts like equivalent noise temperature, available noise power, noise power spectrum density, and methods for measuring noise temperature including the gain method and Y-factor method.
The document describes an FM receiver project. It includes the group members, an overview of radio receivers and how they work, classifications of receivers, details on AM and FM receivers, the circuit diagram and components of the FM receiver, and descriptions of the main sections in the block diagram including the RF amplifier, mixer, filter, IF amplifier, limiter, demodulator, AF amplifier, and oscillator.
This document discusses sampling and related concepts in signal processing. It begins by introducing the need to convert analog signals to discrete-time signals for digital processing. It then covers the sampling theorem, which states that a band-limited signal can be reconstructed if sampled at twice the maximum frequency. The document describes three main sampling methods: ideal (impulse), natural (pulse), and flat-top sampling. It also discusses aliasing, which occurs when a signal is under-sampled. The key aspects of sampling covered are the sampling rate, reconstruction of sampled signals, and anti-aliasing filters.
The document discusses Boolean expressions and their use in computer programming. It defines Boolean expressions as expressions that evaluate to true or false. Boolean expressions are composed of logical operators like AND, OR, and NOT. The document then discusses different logical operators and their truth tables. It also covers Boolean algebra identities and theorems. Finally, it introduces concepts like minterms, maxterms, sum of products, and product of sums and how Karnaugh maps can be used to simplify Boolean expressions.
This document provides an introduction to signals and systems. It defines a signal as a function that carries information about a physical phenomenon, and a system as an entity that processes signals to produce new outputs. Signals can be classified as continuous or discrete, deterministic or random, periodic or aperiodic, even or odd, energy-based or power-based, and causal or noncausal. The document discusses examples and properties of different signal types and how systems manipulate inputs to generate outputs. It covers key concepts like energy, power, periodicity, causality, and system modeling that are important foundations for signals and systems analysis.
Comparator circuits compare two input voltages and produce a logic output signal that is high or low depending on which input is larger. Real comparators do not have an abrupt transition and have very high voltage gain in the transition region. Comparators are often used as interfaces between analog and digital circuits by converting analog signals to logic levels. Open-collector outputs are useful for this by producing either 0V or the supply voltage at their outputs. Schmitt triggers, which are comparators with positive feedback, are commonly used as they introduce hysteresis which helps eliminate unwanted output transitions from noise.
The document discusses different methods for demodulating DSBSC waves, including coherent detection, Costas loop, and squaring loop. Coherent detection extracts the message signal by multiplying the DSBSC wave with a local oscillator signal that is coherent in frequency and phase with the carrier. Costas loop is used to maintain phase coherence between the local oscillator and carrier. Squaring loop recovers the carrier signal by filtering the output of a squaring circuit to extract the signal at twice the carrier frequency.
Este documento trata sobre diferentes tipos de filtros y ecualizadores utilizados en el procesado de señales de audio. Explica conceptos como filtros paso alto y paso bajo, filtros de control de tono, filtros resonantes y banda eliminada. También describe las tecnologías de implementación de filtros, incluyendo filtros pasivos, activos y digitales, y cómo han evolucionado para lograr un factor de calidad constante.
This document outlines a course on pulse and linear integrated circuits taught at Matrusri Engineering College. The course objectives are to analyze linear and non-linear wave shaping circuits, multivibrators, operational amplifiers, and various data converter circuits. The course is divided into units that will cover linear and non-linear wave shaping, attenuators, clipping circuits, clamping circuits, and applications of operational amplifiers and timers. Students will analyze circuit responses to different input signals and learn to design circuits using transistors and operational amplifiers.
The document discusses various types of meters used to measure voltage and current in DC and AC circuits. It describes DC ammeters, which use shunt resistors to measure higher currents beyond the range of the meter movement. Multi-range ammeters use multiple shunts and a range switch to extend the measurement range. DC voltmeters use a series resistor called a multiplier to limit the current through the meter movement. Multi-range voltmeters similarly use multiple multipliers and a range switch. AC meters rectify the input voltage before measuring to obtain the average value using a DC meter. Instrument transformers like current transformers and potential transformers are used to safely measure high currents and voltages in power systems.
This document discusses tracking in receivers. It describes that tracking is the process where the local oscillator frequency follows the signal frequency to maintain the correct intermediate frequency. It explains two types of tracking: two-point tracking using a padder or trimmer capacitor, and three-point tracking which combines both. The purpose of tracking is to minimize any error between the local oscillator and signal frequencies.
A microphone is a transducer that converts sound waves into electrical signals. The quality of a microphone is determined by its characteristics, including sensitivity, signal-to-noise ratio, frequency response, distortion, directivity, and output impedance. Sensitivity measures how well a microphone detects weak sounds, signal-to-noise ratio compares the signal level to the noise floor, and frequency response specifies the range of frequencies accurately reproduced. Ideal microphones have high sensitivity and signal-to-noise ratio, a flat frequency response across most of the audible range, low distortion, and correct output impedance for the application.
Transmission line, single and double matchingShankar Gangaju
This document discusses different types of transmission lines used for transmitting energy and signals over long distances. It describes common transmission line media like twisted pair, coaxial cable and optical fiber. It covers their applications in telephone networks, buildings and computer networks. It also discusses their transmission characteristics and limitations. The document compares properties of unshielded and shielded twisted pair. It provides details on utilizing different wavelengths in optical fiber for various applications.
Here are the steps to find the cutoff frequency:
1) The voltage gain is 3 dB down from the maximum gain at the cutoff frequency.
2) The maximum gain from Step 2 is 4.006 dB.
3) 4.006 dB - 3 dB = 1.006 dB
4) The point on the curve that is 1.006 dB down is the cutoff frequency.
Record this on the curve:
fc = 1.006 dB
fc = 10 kHz
Question: Is the calculated cutoff frequency (fc) in Step 6 equal to the expected cutoff
frequency based on the circuit component values? Explain.
No, the calculated cutoff frequency (10 kHz) in Step 6 is not
This document discusses the generation of frequency modulation (FM) using direct and indirect methods. The direct method uses a reactance modulator like a varactor diode or FET placed across an LC oscillator tank circuit to vary the capacitance or inductance in proportion to the modulating voltage. The indirect method generates FM through phase modulation using a crystal oscillator and phase modulator, then detecting the phase changes to create FM. Vector diagrams are also presented to illustrate phase modulation. Effects of frequency changing like multiplication and mixing on FM signals are explained.
A power amplifier is an electronic device that increases the power of an input signal so it can drive output devices like speakers or radio transmitters. It amplifies low-power signals to a higher power level needed to power external devices. Power amplifiers are used to boost signals to a level sufficient for driving loads such as speakers or transmitting antennas.
This document discusses resonance in series and parallel RLC circuits. It defines key parameters for both circuit types including resonance frequency, half-power frequencies, bandwidth, and quality factor. The series resonance circuit is analyzed showing that impedance is purely resistive at resonance, with maximum current and unity power factor. Parallel resonance is also examined, with admittance being purely conductance at resonance. Formulas for calculating important resonant characteristics are provided.
The document describes MATLAB software and its uses for signal processing. MATLAB is a matrix-based program for scientific and engineering computation. It provides built-in functions for technical computation, graphics, and animation. The Signal Processing Toolbox contains functions for filtering, Fourier transforms, convolution, and filter design. The document lists some important MATLAB commands and frequently used signal processing functions, along with their syntax and purpose. It also describes the basic windows of the MATLAB interface and provides examples of generating common continuous and discrete time signals using MATLAB code.
This document contains information about the Digital Signal Processing lab at Shadan College of Engineering & Technology. It includes:
1. A list of 12 experiments to be conducted in the lab, related to topics like generating signals, implementing filters, and analyzing system responses.
2. An introduction to MATLAB, describing its basic functions and capabilities for numerical computation and signal processing.
3. Programs and instructions for carrying out specific DSP experiments in MATLAB, including generating basic signals, computing the DFT/IDFT of sequences, and determining the impulse/frequency responses of systems defined by difference equations.
The document provides students with an overview of the lab activities and teaches them how to use MATLAB for digital signal
This document contains a lab manual for signals and systems experiments in the Department of Electronics and Communication Engineering at Shadan College of Engineering and Technology. It lists 12 experiments covering topics like frequency spectrum analysis of continuous and discrete signals, frequency response analysis using software and transfer functions, Fourier transforms, convolution, sampling, and filter design. It also provides an introduction to MATLAB, describing basic MATLAB windows, data types, commands, and functions for signals and systems applications.
The document describes implementing the linear convolution of two sequences using MATLAB. Linear convolution involves reflecting one sequence, shifting it, multiplying the sequences element-wise, and summing the results. An example calculates the output of convolving the sequences [1, 2, 3, 1] and [1, 1, 1], yielding the output sequence [1, 3, 6, 6, 4].
Dsp 1recordprophess-140720055832-phpapp01Sagar Gore
This document describes a MATLAB program to study basic operations on discrete-time signals, including amplitude manipulation through scaling, attenuation, reversal, and offsetting, as well as time manipulation through shifting and reflection. The program prompts the user for input signals and operation parameters, performs the selected operations using MATLAB functions, and plots the output signals for comparison.
Digital Signal Processing Lab Manual ECE studentsUR11EC098
This document describes a MATLAB program to perform operations on discrete-time signals. It discusses amplitude manipulation operations like amplification, attenuation, and amplitude reversal. Time manipulation operations covered include time shifting and time reversal. It also describes adding and multiplying two discrete signals. The program takes user input, performs the selected operations, and plots the output waveforms to verify results.
1. Various common signals were generated using MATLAB, including unit impulse, unit step, ramp, sinc, sine, sawtooth, square, and triangular signals. Both continuous and discrete forms were produced.
2. Operations on the generated signals included plotting their amplitude over time or index, adding titles and labels to figures, and displaying the results in different subplot configurations for comparison.
3. Common periodic signals like sine and square waves were generated along with aperiodic signals such as ramp, impulse and step functions to demonstrate the creation of basic continuous and discrete time signals in MATLAB for analysis and simulation.
This technical note explains how you can very easily use the command line functions available in
the MATLAB signal processing toolbox, to simulate simple multirate DSP systems. The focus
here is to be able to view in the frequency domain what is happening at each stage of a system
involving upsamplers, downsamplers, and lowpass filters. All computations will be performed
using MATLAB and the signal processing toolbox. These same building blocks are available in
Simulink via the DSP blockset. The DSP blockset allows better visualization of the overall system,
but is not available in the ECE general computing laboratory or on most personal systems. A
DSP block set example will be included here just so one can see the possibilities with the additional
MATLAB tools.
The document contains details about experiments performed in a Digital Signal Processing practical course. It includes the aims, apparatus required, theory, source code and results for experiments involving MATLAB programs to generate basic signals like impulse, step, ramp and exponential signals; sine and cosine signals; quantization; sampling theorem; linear convolution; autocorrelation; and cross-correlation. Programs were written in MATLAB to perform the various digital signal processing tasks and the output was verified.
This document provides an overview of linear algebra concepts that are important for digital signal processing, including vectors, matrices, norms, inner products, independence, bases and spans. It defines vectors and matrices, and covers properties such as transposes, partitions and norms. Key linear algebra operations for DSP are introduced, such as representing signals and filters using vectors and matrices. The document is the first lecture of a digital signal processing course, setting up fundamental linear algebra concepts to be built upon during the semester.
Digital signal Processing all matlab code with Lab report Alamgir Hossain
Digital signal processing(DSP) laboratory with matlab software....
Problem List :
1.To write a Matlab program to evaluate the impulse response of the system.
2.Computation of N point DFT of a given sequence and to plot magnitude and phase spectrum.
3.To Generate continuous time sinusoidal signal, discrete time cosine signal.
4.To find the DFT / IDFT of given signal.
5.Program for generation of Sine sequence.
6.Program for generation of Cosine sequence.
7. Program for the generation of UNIT impulse signal
8. Program for the generation of Exponential signal.
The document provides an introduction to adaptive filters, which are computational devices that model the relationship between input and output signals in real time to minimize the error between the actual and desired response. It describes the basic elements of adaptive filters including input/output signals, filter structure, coefficients, and adaptive algorithm. It also summarizes common adaptive filter structures like FIR, IIR, and linear combiners and applications such as system identification, inverse modeling, signal prediction, and interference cancellation.
This lab report examines the frequency content of signals using MATLAB. It first analyzes a composite sinusoidal signal made up of two frequencies, plotting the magnitude and power spectrum. It shows the signal contains two peaks at the individual frequencies. It then analyzes a rectangular pulse signal, plotting the magnitude spectrum which takes the form of a sinc function as expected. It also plots the autocorrelation of the pulse signal. The lab report demonstrates using MATLAB to visualize frequency properties of signals.
The document outlines various statistical and data analysis techniques that can be performed in R including importing data, data visualization, correlation and regression, and provides code examples for functions to conduct t-tests, ANOVA, PCA, clustering, time series analysis, and producing publication-quality output. It also reviews basic R syntax and functions for computing summary statistics, transforming data, and performing vector and matrix operations.
Welcome to the Digital Signal Processing (DSP) Lab Manual. This manual is designed to be your comprehensive guide throughout your DSP laboratory sessions. Digital Signal Processing is a fundamental field in electrical engineering and computer science that deals with the manipulation of digital signals to achieve various objectives, such as filtering, transformation, and analysis. In this lab, you will have the opportunity to apply theoretical knowledge to practical, hands-on exercises that will deepen your understanding of DSP concepts.
This manual is structured to provide you with step-by-step instructions, explanations, and insights into the experiments you'll be performing. Each experiment is carefully designed to reinforce your understanding of fundamental DSP principles and help you develop the skills necessary for signal processing applications. Whether you are a student or an instructor, this manual is intended to facilitate a productive and enriching DSP lab experience.
Matlab is a high-level programming language and environment used for numerical computation, visualization, and programming. The document outlines key Matlab concepts including the Matlab screen, variables, arrays, matrices, operators, plotting, flow control, m-files, and user-defined functions. Matlab allows users to analyze data, develop algorithms, and create models and applications.
Welcome to the Digital Signal Processing (DSP) Lab Manual. This manual is designed to be your comprehensive guide throughout your DSP laboratory sessions. Digital Signal Processing is a fundamental field in electrical engineering and computer science that deals with the manipulation of digital signals to achieve various objectives, such as filtering, transformation, and analysis. In this lab, you will have the opportunity to apply theoretical knowledge to practical, hands-on exercises that will deepen your understanding of DSP concepts.
This manual is structured to provide you with step-by-step instructions, explanations, and insights into the experiments you'll be performing. Each experiment is carefully designed to reinforce your understanding of fundamental DSP principles and help you develop the skills necessary for signal processing applications. Whether you are a student or an instructor, this manual is intended to facilitate a productive and enriching DSP lab experience.
This document discusses bulk oil and minimum oil circuit breakers. It defines circuit breakers and explains their need to protect electrical equipment from faults. It describes how bulk oil circuit breakers use oil as both an insulating and interrupting medium, while minimum oil circuit breakers only use a small amount of oil in the interrupting chamber. The document outlines the operation of both types of oil circuit breakers and compares their advantages and disadvantages. Maintenance of oil circuit breakers is also briefly discussed.
1) HVDC transmission was first developed in the late 19th century by Rene Thury. Early systems used DC series generators and mechanical converters.
2) HVDC became more viable with the development of mercury arc valves in the 1950s and thyristor valves in the 1960s, allowing more efficient conversion between AC and DC.
3) HVDC is preferable to HVAC for long distance bulk power transmission, asynchronous connections, offshore wind connections, and other applications where HVDC has technical advantages over HVAC. Key components of HVDC systems include converters, smoothing reactors, filters, and the DC transmission line.
This document provides details on the fabrication of a regulated DC power supply project. It includes a block diagram showing the main components - step down transformer, rectifier, smoothing capacitor and voltage regulators. The circuit diagram and list of components used are also included. The project aims to construct 12V and 5V regulated DC power supplies using a transformer, bridge rectifier, filtering capacitor and IC voltage regulators 7812 and 7805 respectively.
This document provides an overview of production theory and costs. It defines production as the process of converting inputs into outputs. The relationship between inputs and outputs is represented by the production function. There are laws of variable proportions that describe how average and marginal productivity change with increasing input usage in the short-run. In the long-run, returns to scale can be increasing, constant, or decreasing. The document also defines different types of costs including fixed, variable, average, and marginal costs and how they change with output levels in the short-run.
Electrical lamps have several advantages over mechanical lamps including cleanliness, easy control, lower cost, ease of use, steady output, reliability, and suitability for many purposes. Common electrical lighting types discussed in the document include incandescent, fluorescent, high intensity discharge, and light emitting diode lamps. Incandescent lamps work by passing current through a tungsten filament to produce light, while fluorescent lamps use mercury and phosphors to convert ultraviolet light into visible light. Tungsten-halogen lamps improve on incandescent efficiency through the use of halogen gases.
This document provides details about an industrial visit by engineering students to the Ukai Hydro Power Plant in Gujarat, India. It includes an introduction to the Ukai plant, which has a 300 MW installed capacity across 4 units. The document also contains an acknowledgements section thanking those who supported and guided the visit, as well as sections on the history, basic principles, site selection, construction, working, main parts, advantages, and disadvantages of hydro power plants.
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Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
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This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
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Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
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An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
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The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Your Skill Boost Masterclass: Strategies for Effective Upskilling
signal and system
1. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 1
Babaria Institute of Technology
Electrical Engineering Department
Semester :4 Branch:EE
Subject: Signals & Systems (2141005) Experiment No. 1
Aim: To familiarize with MATLAB software, general functions and signal processing
toolbox functions.
The name MATLAB stands for MATrix LABoratory produced by Mathworks Inc., USA. It is a
matrix-based powerful software package for scientific and engineering computation and
visualization. Complex numerical problems can be solved in a fraction of the time that
required with other high level languages. It provides an interactive environment with
hundreds of built -in –functions for technical computation, graphics and animation. In
addition to built-in-functions, user can create his own functions.
MATLAB offers several optional toolboxes, such as signal processing, control systems, neural
networks etc. It is command driven software and has online help facility.
MATLAB has three basic windows normally; command window, graphics window and edit
window.
Command window is characterized by the prompt ‘>>’.
All commands and the ready to run program filename can be typed here. Graphic window
gives the display of the figures as the result of the program. Edit window is to create
program files with an extension .m.
Some important commands in MATLAB
Help : List topics on which help is available
Help command name: Provides help on the topic selected
Demo : Runs the demo program
Who : Lists variables currently in the workspace
Whos : Lists variables currently in the workspace with their size
Clear : Clears the workspace, all the variables are removed
Clear x,y,z : Clears only variables x,y,z
Quit: Quits MATLAB
2. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 2
Some of the frequently used built-in-functions in Signal Processing Toolbox
filter(b.a.x): Syntax of this function is Y = filter(b.a.x)
It filters the data in vector x with the filter described by vectors
a and b to create the filtered data y.
fft (x): It is the DFT of vector x
ifft (x) : It is the DFT of vector x
conv (a,b) : Syntax of this function is C = conv (a,b)
It convolves vectors a and b. The resulting vector is ofLength,
Length (a) + Length (b)-1
deconv(b,a): Syntax of this function is [q,r] = deconv(b,a)
It deconvolves vector q and the remainder in vector r such that
b = conv(a,q)+r
butter(N,Wn): Designs an Nth order lowpass digital Butterworth filter and
returns the filter coefficients in length N+1 vectors B
(numerator) and A (denominator). The coefficients are listed in
descending powers of z. The cutoff frequency Wn must be 0.0
< Wn < 1.0, with 1.0 corresponding tohalf the sample rate.
buttord(Wp, Ws, Rp, Rs): Returns the order N of the lowest order digital Butterworth
filter that loses no more than Rp dB in the passband and has at
least Rs dB of attenuation in the stopband. Wp and Ws are the
passband and stopband edge frequencies, Normalized from 0
to 1 ,(where 1 corresponds to pi rad/sec)
Cheby1(N,R,Wn) : Designs an Nth order lowpass digital Chebyshev filter with R
decibels of peak-to-peak ripple in the passband. CHEBY1
returns the filter coefficients in length N+1 vectors B
(numerator) and A (denominator). The cutoff frequency Wn
must be 0.0 < Wn < 1.0, with 1.0 corresponding to half the
sample rate.
Cheby1(N,R,Wn,'high'): Designs a highpass filter.
3. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 3
Cheb1ord(Wp, Ws, Rp, Rs): Returns the order N of the lowest order digital Chebyshev
Type I filter that loses no more than Rp dBin the passband and
has at least Rs dB of attenuation in the stopband. Wp and Ws
are the passband and stopband edge frequencies, normalized
from 0 to 1 (where 1 corresponds to pi radians/sample)
cheby2(N,R,Wn) : Designs an Nth order lowpass digital Chebyshev filter with the
stopband ripple R decibels down and stopband edge
frequency Wn. CHEBY2 returns the filter coefficients in length
N+1 vectors B (numerator) and A. The cutoff frequency Wn
must be 0.0 < Wn < 1.0, with 1.0 corresponding to half the
sample rate.
cheb2ord(Wp, Ws, Rp, Rs): Returns the order N of the lowest order digital Chebyshev
Type II filter that loses no more than Rp dB in the passband
and has at least Rs dB of attenuation in the stopband. Wp and
Ws are the passband and stopband edge frequencies.
abs(x): It gives the absolute value of the elements of x. When x is
complex, abs(x) is the complex modulus (magnitude) of the
elements of x.
angle(H): It returns the phase angles of a matrix with complex elements
in
radians.
freqz(b,a,N) : Syntax of this function is [h,w] = freqz(b,a,N) returns the
Npoint
frequency vector w in radians and the N-point complex
frequency response vector h of the filter b/a.
stem(y) : It plots the data sequence y aa stems from the x axis
terminated
with circles for the data value.
stem(x,y): It plots the data sequence y at the values specified in x.
ploy(x,y) : It plots vector y versus vector x. If x or y is a matrix, then the
vector is plotted versus the rows or columns of the
matrix,cwhichever line up.
title(‘text’): It adds text at the top of the current axis.
xlabel(‘text’): It adds text beside the x-axis on the current axis.
ylabel(‘text’): It adds text beside the y-axis on the current axis.
4. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 4
Experiment :2
To plot graph of Continuous Time Signals
5. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 5
Unit step function
Program :
T=30;
x=ones(1,T);
t=0:1:T-1
plot(t,x);
grid on;
xlabel('time(sec)')
ylabel('x(t)')
Output :
0 5 10 15 20 25 30
0
0.5
1
1.5
2
time(sec)
x(t)
6. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 6
Unit ramp function
Program :
t=0:0.03:4;
x=t;
plot(t,x)
grid on;
xlabel('Time(sec)')
ylabel('x(t)')
Output :
0 1 2 3 4
0
1
2
3
4
Time(sec)
x(t)
7. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 7
Unit parabolic function
Program :
t=0:0.01:2;
x=t.^2/2;
plot(t,x);
grid on;
xlabel('Time(sec)')
ylabel('x(t)')
Output :
0 0.5 1 1.5 2
0
0.5
1
1.5
2
Time(sec)
x(t)
8. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 8
Impulse function
Program :
for t = 0;
x = 1;
end;
plot(t,x);
stem(t,x)
grid on;
xlabel('Time(sec)')
ylabel('x(t)')
Output :
-1 -0.5 0 0.5 1
0
0.2
0.4
0.6
0.8
1
Time(sec)
x(t)
9. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 9
Rectangular pulse function
Program :
t=-1:0.001:1;
x=rectpuls(t);
plot(t,x);
grid on;
xlabel('Time(sec)')
ylabel('x(t)')
Output :
-1 -0.5 0 0.5 1
0
0.2
0.4
0.6
0.8
1
Time(sec)
x(t)
10. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 10
Triangular pulse function
Program :
t=-1:0.002:1;
x=tripuls(t);
plot(t,x);
grid on;
xlabel('Time(sec)')
ylabel('x(t)')
Output:
Signum function
-1 -0.5 0 0.5 1
0
0.2
0.4
0.6
0.8
1
Time(sec)
x(t)
32. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 32
Experiment :04
To perform signal operation using
stimulink
33. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 33
Program : u(t)-u(t-1)
Output :
34. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 34
Program : r(t)-2r(t-1)+r(t-2)
Output :
35. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 35
Program : r(t)-2u(t-1)-r(t-2)
Output :
36. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 36
Program : r(t)-r(t-1)-u(t-1)
Output :
37. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 37
Experiment :05
To perform the convolution sum
of discrete time signal.
38. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 38
Program :
a=[ 1 -1 2 3];
b=[ 1 -2 3 -1];
z=conv(a,b);
m=length(z);
y=0:m-1;
stem(y,z);
Output :
0 1 2 3 4 5 6
-5
0
5
10
a
b
39. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 39
Program :
a=[ 1 2 3 2];
b=[ 1 2 2];
z=conv(a,b);
m=length(z);
y=0:m-1;
stem(y,z);
Output :
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
0
5
10
15
a
b
40. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 40
Program :
a=[ 1 4 3 2];
b=[ 1 3 2 1];
z=conv(a,b);
m=length(z);
y=0:m-1;
stem(y,z);
Output :
0 1 2 3 4 5 6
0
5
10
15
20
a
b
42. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 42
Experiment :06
To perform z-transform using
MATLAB
43. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 43
Program :
syms f n;
f=2^n;
ztrans(f);
Output :
z/(z - 2)
Program :
syms f n w;
f=cos(n);
ztrans(f);
Output :
(z*(z - cos(1)))/(z^2 - 2*cos(1)*z + 1)
44. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 44
Program :
syms f n w;
f=2^n+3^n;
ztrans(f);
Output :
z/(z - 2) + z/(z - 3)
Program :
syms f n w;
f=(n^2)*(2^n);
ztrans(f);
Output :
(z^2/4 + z/2)/(z/2 - 1)^3
45. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 45
Experiment :07
To plot zeros and poles in the z-plane
using MATLAB.
46. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 46
Program :
syms n d z
n=[1 1];
d=[1 2 3 4];
sys=tf(n,d),disp(z);
zplane(n,d);
Output :
s + 1
s^3 + 2 s^2 + 3 s + 4
-2 -1.5 -1 -0.5 0 0.5 1 1.5
-1.5
-1
-0.5
0
0.5
1
1.5
2
Real Part
ImaginaryPart
47. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 47
Program :
syms n d z
n=[1 0.5];
d=[1 1 1];
sys=tf(n,d),disp(z);
zplane(n,d);
Output :
s + 0.5
s^2 + s + 1
-1.5 -1 -0.5 0 0.5 1 1.5
-1
-0.5
0
0.5
1
Real Part
ImaginaryPart
48. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 48
Program :
syms n d z
n=[3 0];
d=[1 6 9];
sys=tf(n,d),disp(z);
zplane(n,d);
Output :
3 s
s^2 + 6 s + 9
-3 -2 -1 0 1
-1
-0.5
0
0.5
1
22
Real Part
ImaginaryPart
49. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 49
Program :
syms n d z
n=[1 1 0];
d=[1 3 1 1];
sys=tf(n,d),disp(z);
zplane(n,d);
Output :
s^2 + s
s^3 + 3 s^2 + s + 1
-2.5 -2 -1.5 -1 -0.5 0 0.5 1
-1
-0.5
0
0.5
1
2
Real Part
ImaginaryPart
50. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 50
Experiment -08
To perform FFT using MATLAB.
51. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 51
1. Program:
a = input('enter sequence');
b = length(a);
x = fft(a,b)
Output:
Enter sequence[1 2 3 4]
x =
10.0000 -2.0000 + 2.0000i -2.0000 -2.0000 - 2.0000i
2. Program :
a = input('enter sequence');
b = length(a);
x = fft(a,b)
Output :
enter sequence[5 7 9 5]
x =
26.0000 -4.0000 - 2.0000i 2.0000
-4.0000 + 2.0000i
52. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 52
Experiment -09
To perform IFFT using MATLAB.
53. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 53
1. Program:
a = input('Enter sequence');
b = length(a);
x = ifft(a,b)
Output:
Enter sequence[1 2 3 4]
x =
2.5000 -0.5000 - 0.5000i -0.5000
-0.5000 + 0.5000i
2. Program :
a = input('Enter sequence');
b = length(a);
x = ifft(a,b)
Output:
Enter sequence[2 5 8 6]
x =
5.2500 -1.5000 - 0.2500i -0.2500
-1.5000 + 0.2500i
54. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 54
Experiment - 10
To verify sampling theorem using
MATLAB.
55. SIGNALS & SYSTEMS (2141005) EXPERIMENT- 1
ELECTRICALDEPARTMENT
BITS EDU CAMPUS Page 55
Program:
T=0.04; % Time period of 50 Hz
signal
t=0:0.0005:0.02;
f = 1/T;
n1=0:40;
size(n1)
xa_t=sin(2*pi*2*t/T);
plot(200*t,xa_t);
title('Continuous signal');
grid on;
xlabel('t');
ylabel('x(t)');
Output:
0 0.5 1 1.5 2 2.5 3 3.5 4
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Continuous signal
t
x(t)