1. data and signals
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This document discusses analog and digital data and signals, and the three main causes of transmission impairment: attenuation, distortion, and noise. It defines analog and digital data as being continuous or discrete, respectively. Attenuation refers to the loss of energy as a signal travels through a medium. Distortion occurs when different frequency components of a composite signal travel at different speeds, arriving with different phases. Noise comes from various sources like thermal effects, induced interference, crosstalk, and impulses. Figures are provided to illustrate these concepts of analog and digital signals, attenuation, distortion, and the different types of noise.
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4.programmable dma controller 8257
This document provides an overview of the Intel 8257 Programmable DMA Controller. It describes how DMA operations are performed by allowing devices to directly access memory without CPU interference. It details the key features of the 8257 including its 4 channels, 16-bit addressing, and transfer modes. The document also includes diagrams of the 8257 architecture and pin connections. It concludes with advantages of DMA including faster transfer speeds and reduced CPU overhead, as well as disadvantages such as implementation costs.
3.programmable interrupt controller 8259
The document describes the Intel 8259 programmable interrupt controller chip. It contains blocks for buffering data to and from the system data bus, controlling read/write signals, storing interrupt requests in the interrupt request register, masking interrupts in the interrupt mask register, tracking interrupts being serviced in the in-service register, resolving interrupt priorities, and cascading multiple 8259 chips. The pin diagram shows inputs for interrupt requests, read/write control, an ID comparator for cascading, and an 8-bit data bus.
1.ppi 8255
The document provides information about the Intel 8255 Programmable Peripheral Interface chip. It includes a block diagram and descriptions of the main components. The 8255 has 3 8-bit ports (A, B, C) that can be configured in different operating modes for input/output. It describes the pin functions and how the 8255 can interface with the Intel 8085 microprocessor. The main operating modes - I/O, bit set/reset, and the various configurations for ports A, B and C in each mode - are summarized.
Topic4 data encryption standard(des)
The document discusses the Data Encryption Standard (DES), including:
- DES is a block cipher that encrypts data in 64-bit blocks using a 56-bit key and 16 rounds of encryption.
- DES has a block size of 64 bits, a key size of 56 bits (though the key specification is 64 bits with 8 bits used for error checking), and uses 16 intermediate 48-bit keys over its 16 rounds.
- The DES encryption process uses substitution boxes (S-boxes) to encrypt each block, and has 4 known weak keys that should be avoided during key generation.
Topic3 playfain
1. The document summarizes the Playfair cipher and Vigenere cipher. The Playfair cipher encrypts text as digraphs (pairs of letters) using a 5x5 grid, while the Vigenere cipher uses a polyalphabetic substitution cipher where the alphabet is shifted according to a repeating keyword.
2. The Playfair cipher encryption involves splitting the plaintext into pairs, and then looking at the letters' positions in the grid to determine which letters to substitute. If both letters are in the same row/column, letters are taken from that row/column. Otherwise, a rectangle is formed to find the substitution.
3. The Vigenere cipher adds the letters of the plaintext and keyword modulo 26
Topic2 caser hill_cripto
This document discusses the Caesar cipher and Hill cipher methods of encryption. It provides an introduction to each cipher, including how the Caesar cipher works by shifting letters of the alphabet and how the Hill cipher uses a matrix to encrypt blocks of text. The key advantages and disadvantages of each cipher are outlined, such as the Caesar cipher being very easy to implement but also easy to hack, while the Hill cipher provides more security but encrypted text cannot be decrypted if the key matrix is noninvertible. Examples of encrypting and decrypting text using each cipher are also included.
Topic5 advanced encryption standard (aes)
1) The Advanced Encryption Standard (AES) is a symmetric block cipher chosen by the U.S. government to protect classified information. It operates on 128-bit blocks using 128, 192, or 256-bit keys.
2) AES encryption works by first dividing plaintext into blocks, then adding an initial round key. It undergoes multiple rounds of byte substitution, shift rows, mix columns, and XOR with round keys until ciphertext is produced.
3) Proper implementation and protection of AES encryption keys is important for security, as keys could enable hackers to decrypt ciphertext if accessed without authorization.
Topic1 substitution transposition-techniques
This document discusses substitution and transposition encryption techniques. Substitution techniques replace plaintext characters with other characters, numbers, or symbols, changing character identity but not position. Transposition techniques rearrange the character positions in the plaintext, changing character position but not identity. Examples of substitution techniques include the Caesar cipher, monoalphabetic ciphers, Playfair cipher, and Vigenère cipher. Transposition techniques examples are the rail fence cipher and row transposition cipher.
11. lzw coding
This document provides an overview of LZW coding technique for image compression. It discusses that LZW coding is a lossless compression scheme used for formats like GIF, TIFF, and PDF. It works by assigning the first 256 values (0-255) in an 8-bit grayscale image to a dictionary, and then adding new sequences encountered in the image to the dictionary. As the image is scanned, the encoded output consists of dictionary entries. The document provides an example and illustrates the encoding process. It notes advantages like high compression ratios without needing probability knowledge, and disadvantages like potential unused dictionary entries. It concludes that LZW can be used to compress files like TIFF, GIF, PDF, and text files.
9. hofman coding in DIP
This document discusses Huffman coding for image compression. It explains that image compression reduces data storage requirements by decreasing redundancies in image representation without visually reducing image quality. Huffman coding builds a tree by combining the two bins with the lowest histogram values until one bin remains, encodes the tree, and then encodes the residual image. Examples are provided to illustrate the Huffman coding algorithm. The summary notes that Huffman coding achieves minimal redundancy by sorting symbols by probability and assigning codewords at each node of the binary tree.
7. image enhancement using spatial filtering
This document discusses spatial filtering for image enhancement. It begins by introducing filters and explaining that filtering can modify or enhance images by highlighting certain features or removing others. It then explains that spatial filtering involves applying a filter mask to an image point by point. The mechanism of spatial filtering is described as calculating filter responses at each point (x,y) using a predefined relationship between pixels under the mask and mask coefficients. Linear spatial filtering is discussed where each pixel is replaced by a constant value. Convolution is introduced as the process of applying filters to an image. The approaches and types of spatial filtering are outlined. In summary, spatial filtering uses a mask that is applied point by point to an image to calculate new pixel values using neighboring pixel values and
5. gray level transformation
This document discusses different types of gray level transformations that are commonly used in image processing. It describes three main types of transformations: linear, logarithmic, and power-law transformations. Linear transformations include identity and negative transformations. Logarithmic transformations include log and inverse log transformations. Power-law transformations include nth power and nth root transformations which are also known as gamma transformations, where the gamma value determines whether darker or brighter images are produced. Examples of transformations with different gamma values are also shown.
1. steps in image processing
Digital image processing involves processing digital images using a computer. It defines a digital image as a two-dimensional function where intensity values are discrete quantities. The fundamental steps in digital image processing are image acquisition, enhancement, restoration, compression, morphological operations, segmentation, and representation and description. Image enhancement improves image quality, restoration fixes degraded images, and compression reduces file size for storage and transmission with minimal information loss.
5. convolution and correlation of discrete time signals
This document discusses convolution and correlation of discrete time signals. It defines convolution as a mathematical way of combining two signals to form a third signal, which is equivalent to finite impulse response filtering. Convolution relates the input, output, and impulse response of a linear time-invariant system. The document also provides examples of discrete linear convolution and periodic convolution. It then defines correlation as a measure of similarity between signals, discussing cross-correlation and auto-correlation, and providing examples of calculating each.
4. operations of signals
This document discusses various operations that can be performed on signals, including time shifting, time reversal, time scaling, signal addition, and signal multiplication. It provides examples and explanations of each operation. Time shifting involves shifting a signal along the time axis. Time reversal involves reversing a signal along the time axis. Time scaling involves compressing or expanding a signal along the time axis. Signal addition and multiplication involve combining two signals by adding or multiplying their corresponding sample values.
3. systems
This document defines and describes different types of systems. A system takes a signal as input and transforms it into an output signal. There are several ways to classify systems, including whether they are static or dynamic, causal or non-causal, linear or non-linear, time-invariant or time-varying, stable or unstable, and invertible or non-invertible. For example, a static system is memoryless and its output depends only on the present input values, while a dynamic system is one with memory where the output depends on past and future input values.
2. classification of signals
This document discusses different types of signals. It defines a signal as a function that conveys information about a physical phenomenon. Signals can be one-dimensional or multi-dimensional depending on the number of variables. Both continuous and discrete signals are further classified as deterministic or random, periodic or non-periodic, energy or power signals, causal or non-causal, and even or odd. Deterministic signals have predictable behavior while random signals do not. Periodic signals repeat after a time period versus non-periodic signals. Energy signals have finite energy and zero power, while power signals have infinite energy. Causal signals are zero for negative time indexes and non-causal signals exist for both positive and negative time.
1. elementary signals
This document discusses elementary signals that are basic building blocks for more complex signals in signal and systems analysis. It identifies six types of elementary signals: unit step, unit ramp, unit parabolic, unit impulse, sinusoidal, and real exponential sequences. Each signal type is defined, with the unit step existing only for positive time, the unit ramp increasing linearly over time, the unit parabolic following a quadratic function, and the unit impulse being equal to one only at time zero. The document also notes that sinusoidal sequences can be periodic or not depending on frequency, and that real exponential sequences grow, decay, or alternate based on their constant value.
4. random number and it's generating techniques
Random numbers are numbers generated unpredictably and cannot be reproduced sequentially. They are important for simulation tasks. Pseudo-random numbers aim to imitate true random numbers by producing numbers uniformly between 0 and 1 using algorithms. Common techniques for generating pseudo-random numbers include the linear congruential method (LCM), combined linear congruential generators (CLCG), and random number streams. The LCM produces integers between 0 and a modulus using a recursive relationship based on a seed, multiplier, and increment. CLCG combine multiple LCMs to achieve longer periods by summing their outputs. Random number streams refer to portions of a generator's sequence dedicated to specific purposes to allow comparison of alternative systems.
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1. data and signals
- 1. Data and signals By Md. Fazle Rabbi 16CSE057
- 2. 4.2 ANALOG AND DIGITAL • Data can be analog or digital. • The term analog data refers to information that is continuous; • digital data refers to information that has discrete states. • Analog data take on continuous values. • Digital data take on discrete values.
- 3. 4.3 Analog and Digital Data Analog and Digital Signals Topics discussed in this section: Attenuation Distortion Noise TRANSMISSION IMPAIRMENT
- 4. 4.4 Analog and Digital Data Data can be analog or digital. Analog data are continuous and take continuous values. Digital data have discrete states and take discrete values.
- 5. 4.5 Analog and Digital Signals •Signals can be analog or digital. •Analog signals can have an infinite number of values in a range. •Digital signals can have only a limited number of values.
- 6. 4.6 Figure 1 Comparison of analog and digital signals
- 7. 4.7 Signals travel through transmission media, which are not perfect. The imperfection causes signal impairment. This means that the signal at the beginning of the medium is not the same as the signal at the end of the medium. What is sent is not what is received. Three causes of impairment are attenuation, distortion, and noise. Figure 2 Causes of impairment
- 8. 4.8 Attenuation • Means loss of energy -> weaker signal • When a signal travels through a medium it loses energy overcoming the resistance of the medium • Amplifiers are used to compensate for this loss of energy by amplifying the signal.
- 9. 4.9 Measurement of Attenuation • To show the loss or gain of energy the unit “decibel” is used. dB = 10log10P2/P1 P1 - input signal P2 - output signal
- 11. 4.11 Distortion • Means that the signal changes its form or shape • Distortion occurs in composite signals • Each frequency component has its own propagation speed traveling through a medium. • The different components therefore arrive with different delays at the receiver. • That means that the signals have different phases at the receiver than they did at the source.
- 13. 4.13 Noise • There are different types of noise • Thermal - random motion of electrons in the wire creates an extra signal • Induced - from motors and appliances, devices act as transmitter antenna and medium as receiving antenna. • Crosstalk - same as above but between two wires. • Impulse - Spikes that result from power lines, lightning, etc.
- 15. 4.15 Thank you