Describe the non linear dynamic pipeline concepts, Creation of reservation table from non-linear pipeline architecture, creation of collision vector from reservation table, generation of state diagram, derivation of simple cycles, greedy cycles and MAL(Minimum Average Latency)
block diagram representation of control systemsAhmed Elmorsy
This document provides an introduction to block diagram representation of control systems. It discusses how block diagrams provide a pictorial representation of the relationships between elements in a system using blocks and arrows. The blocks represent system elements or operations, and the arrows represent the direction of signal or information flow. Specific topics covered include summing points, takeoff points, examples of representing equations as block diagrams, and canonical forms.
This presentation discusses transfer functions. It defines a transfer function as the ratio of the Laplace transform of the output to the Laplace transform of the input with all initial conditions equal to zero. It classifies transfer functions as proper, strictly proper, or improper based on the order of the numerator and denominator polynomials. Poles and zeros are also discussed as values of s that make the transfer function tend to infinity or zero. The presentation provides examples of finding the transfer function of electrical and mechanical systems using differential equations. Advantages and disadvantages of using transfer functions to model systems are also summarized.
This document discusses techniques for reducing block diagrams and signal flow graphs that represent complex control systems composed of multiple interconnected subsystems into a single transfer function. It introduces block diagram elements like summing junctions and pickoff points used to represent interconnections. Three methods for reducing block diagrams to an equivalent transfer function are presented: cascade form, parallel form, and feedback form. Rules are provided for moving blocks around diagrams to establish these familiar forms. Signal flow graphs are introduced as an alternative representation and Mason's rule is outlined as a method for reducing a signal flow graph to a transfer function. Examples are worked through to demonstrate these reduction techniques.
This document outlines a lecture on block diagrams for a control systems engineering course. It begins with an introduction to block diagrams and their use in representing subsystems and combining multiple subsystems. It provides examples of subsystems for automobile control and antenna control. The document then discusses mathematical modeling of systems using transfer functions. It covers concepts such as cascaded systems, feedback forms, and simplifying block diagrams. Finally, it provides examples of simplifying complex block diagrams and modeling a shuttle pitch control system using block diagrams.
This document contains a presentation on block diagram representation and reduction techniques. It discusses how block diagrams can be used to represent complex systems through interconnected blocks, each characterized by a transfer function. The key advantages and disadvantages of using block diagrams are outlined. The document then covers topics such as closed loop systems, drawing block diagrams, and provides step-by-step examples of applying block reduction techniques to derive an equivalent transfer function.
This document summarizes the design of microwave filters using composite, m-derived, T-network, and π-network sections. It describes:
1) How constant-k sections have very slow attenuation rates and non-constant image impedances. M-derived sections are introduced to address this by replacing component values to obtain the same image impedance as the constant-k section.
2) The propagation constant and image impedance equations for low-pass and high-pass T-network and π-network constant-k and m-derived sections.
3) Composite filters formed by combining m-derived and constant-k sections act as proper filters with rapid initial attenuation that does not reduce at higher
This document discusses system design methodologies including finite state machines (FSMs), register transfer level (RTL) design using algorithmic state machine (ASM) charts and the datapath and controller design approach. It provides examples of modeling styles for FSMs and ASM charts in Verilog. Specifically, it describes modeling a pattern detector FSM and implementing the Booth multiplication algorithm using an ASM chart, which is then transformed into a datapath and controller architecture.
Describe the non linear dynamic pipeline concepts, Creation of reservation table from non-linear pipeline architecture, creation of collision vector from reservation table, generation of state diagram, derivation of simple cycles, greedy cycles and MAL(Minimum Average Latency)
block diagram representation of control systemsAhmed Elmorsy
This document provides an introduction to block diagram representation of control systems. It discusses how block diagrams provide a pictorial representation of the relationships between elements in a system using blocks and arrows. The blocks represent system elements or operations, and the arrows represent the direction of signal or information flow. Specific topics covered include summing points, takeoff points, examples of representing equations as block diagrams, and canonical forms.
This presentation discusses transfer functions. It defines a transfer function as the ratio of the Laplace transform of the output to the Laplace transform of the input with all initial conditions equal to zero. It classifies transfer functions as proper, strictly proper, or improper based on the order of the numerator and denominator polynomials. Poles and zeros are also discussed as values of s that make the transfer function tend to infinity or zero. The presentation provides examples of finding the transfer function of electrical and mechanical systems using differential equations. Advantages and disadvantages of using transfer functions to model systems are also summarized.
This document discusses techniques for reducing block diagrams and signal flow graphs that represent complex control systems composed of multiple interconnected subsystems into a single transfer function. It introduces block diagram elements like summing junctions and pickoff points used to represent interconnections. Three methods for reducing block diagrams to an equivalent transfer function are presented: cascade form, parallel form, and feedback form. Rules are provided for moving blocks around diagrams to establish these familiar forms. Signal flow graphs are introduced as an alternative representation and Mason's rule is outlined as a method for reducing a signal flow graph to a transfer function. Examples are worked through to demonstrate these reduction techniques.
This document outlines a lecture on block diagrams for a control systems engineering course. It begins with an introduction to block diagrams and their use in representing subsystems and combining multiple subsystems. It provides examples of subsystems for automobile control and antenna control. The document then discusses mathematical modeling of systems using transfer functions. It covers concepts such as cascaded systems, feedback forms, and simplifying block diagrams. Finally, it provides examples of simplifying complex block diagrams and modeling a shuttle pitch control system using block diagrams.
This document contains a presentation on block diagram representation and reduction techniques. It discusses how block diagrams can be used to represent complex systems through interconnected blocks, each characterized by a transfer function. The key advantages and disadvantages of using block diagrams are outlined. The document then covers topics such as closed loop systems, drawing block diagrams, and provides step-by-step examples of applying block reduction techniques to derive an equivalent transfer function.
This document summarizes the design of microwave filters using composite, m-derived, T-network, and π-network sections. It describes:
1) How constant-k sections have very slow attenuation rates and non-constant image impedances. M-derived sections are introduced to address this by replacing component values to obtain the same image impedance as the constant-k section.
2) The propagation constant and image impedance equations for low-pass and high-pass T-network and π-network constant-k and m-derived sections.
3) Composite filters formed by combining m-derived and constant-k sections act as proper filters with rapid initial attenuation that does not reduce at higher
This document discusses system design methodologies including finite state machines (FSMs), register transfer level (RTL) design using algorithmic state machine (ASM) charts and the datapath and controller design approach. It provides examples of modeling styles for FSMs and ASM charts in Verilog. Specifically, it describes modeling a pattern detector FSM and implementing the Booth multiplication algorithm using an ASM chart, which is then transformed into a datapath and controller architecture.
it is a lab manual, normally in various colleges filter designing is "Black-Sheep" on subjects. because many of the students failed in this exam.
it is very helpful to them.
this presentation will help u with understanding basic elements of the bloc diagram and how to reduce multi loop block diagram with some suitable numerical example.
Reduction of multiple subsystem [compatibility mode]azroyyazid
This document discusses techniques for reducing multiple subsystems to a single transfer function. It covers block diagram algebra and Manson's rule. Block diagram algebra can be used to reduce block diagrams representing cascaded, parallel, and feedback subsystems into equivalent single transfer functions. The key techniques are collapsing summing junctions and forming equivalent cascaded, parallel, and feedback systems. Signal-flow graphs also represent subsystems and can be reduced using Manson's rule by writing equations for each signal as the sum of incoming signals times their transfer functions. Examples demonstrate reducing various block diagrams and signal-flow graphs to equivalent single transfer functions.
The document describes the Newton-Raphson method for finding the roots of functions. It provides the derivation and algorithm for the method. An example problem is worked through, showing the estimates converging to a root over multiple iterations. Some potential drawbacks of the method are discussed, including divergence at inflection points, division by zero, oscillations near local extrema, and root jumping.
A block diagram uses blocks and lines to show the related functions of parts of an electric circuit or system. Such a diagram shows the normal order of progression of the signal through a circuit.
A system is an assembly of parts (components) connected together to perform a stated function.
The system may be comprises of:
• A number of individual components connected together
• A number of smaller units called subsystem.
o Each subsystem itself consists of individual parts
The document discusses frequency response and Bode plots. It begins by defining the sinusoidal transfer function and frequency response. The frequency response consists of the magnitude and phase functions of the transfer function. Bode plots graphically display the magnitude and phase functions versus frequency on logarithmic scales. The document then provides procedures for constructing Bode plots, including determining individual component responses, combining them, and reading off gain and phase margins. Examples are given to demonstrate the procedures.
This document discusses the time response of second order systems. It begins by defining key terms like natural frequency, damped frequency, and damping factor. It then analyzes the time response based on the value of the damping factor, categorizing systems as underdamped, undamped, critically damped, or overdamped. Underdamped systems oscillate with decaying amplitude, undamped systems oscillate without decay, critically damped systems decay exponentially without oscillation, and overdamped systems decay exponentially with two distinct time constants. Equations for the time response are derived for each case.
Computation of Electromagnetic Fields Scattered from Dielectric Objects of Un...Alexander Litvinenko
1) The document describes a method called Multilevel Monte Carlo (MLMC) to efficiently compute electromagnetic fields scattered from dielectric objects of uncertain shapes. MLMC balances statistical errors from random sampling and numerical errors from geometry discretization to reduce computational time.
2) A surface integral equation solver is used to model scattering from dielectric objects. Random geometries are generated by perturbing surfaces with random fields defined by spherical harmonics.
3) MLMC is shown to estimate scattering cross sections accurately while requiring fewer overall computations compared to traditional Monte Carlo methods. This is achieved by optimally allocating samples across discretization levels.
SIGNIFICANCE OF BLOCK DIAGRAM AND SIGNAL FLOW GRAPH IN CONTROL SYSTEMDinesh Sharma
This document discusses block diagrams and signal flow graphs, which are useful tools for modeling control systems. It begins by explaining what block diagrams are and how they represent the components and signal flows in a system. Signal flow graphs are then introduced as a more compact way to determine the relationships between input and output variables using Mason's gain formula, without needing to reduce the diagram. The document provides examples of block diagram reductions and simple signal flow graphs. It concludes that block diagrams and signal flow graphs provide control engineers a better understanding of systems by describing the connections between components.
This document discusses block diagram representation. It begins by defining a block diagram as a pictorial representation of the cause-and-effect relationship of a system. Block diagrams show the components, direction of information flow with arrows, and can describe the function of each block. Block diagrams are useful for analyzing and designing control systems, but do not provide unique representations or show the physical construction or energy sources of a system. The document also discusses techniques for reducing block diagrams, such as combining or moving blocks.
This document provides information about a Control Systems Theory course, including:
- The assessment breakdown is 20% mini project, 20% lab report, 20% test, and 40% final exam.
- The teaching plan covers topics like system representation, response analysis, stability analysis, and controller design over 14 weeks.
- The objectives are to understand control systems concepts and evaluate system responses.
- Control systems are used to amplify power, allow remote control, improve input/output forms, and compensate for disturbances. Examples given include elevators, cruise control, ABS, and vehicle suspension.
On the principle of optimality for linear stochastic dynamic systemijfcstjournal
In this work, processes represented by linear stochastic dynamic system are investigated and by
considering optimal control problem, principle of optimality is proven. Also, for existence of optimal
control and corresponding optimal trajectory, proofs of theorems of necessity and sufficiency condition are
attained.
Multiple Sensors Soft-Failure Diagnosis Based on Kalman Filtersipij
Sensor is the necessary components of the engine control system. Therefore, more and more work must do for improving sensors reliability. Soft failures are small bias errors or drift errors that accumulate relatively slowly with time in the sensed values that it must be detected because of it can be very easy to be mistaken for the results of noise. Simultaneous multiple sensors failures are rare events and must be considered. In order to solve this problem, a revised multiple-failure-hypothesis based testing is investigated. This approach uses multiple Kalman filters, and each of Kalman filter is designed based on a specific hypothesis for detecting specific sensors fault, and then uses Weighted Sum of Squared Residual (WSSR) to deal with Kalman filter residuals, and residual signals are compared with threshold in order to make fault detection decisions. The simulation results show that the proposed method can be used to detect multiple sensors soft failures fast and accurately.
Introduction to Convolutional Codes
Convolutional Encoder Structure
Convolutional Encoder Representation(Vector, Polynomial, State Diagram and Trellis Representations )
Maximum Likelihood Decoder
Viterbi Algorithm
MATLAB Simulation
Hard and Soft Decisions
Bit Error Rate Tradeoff
Consumed Time Tradeoff
This document discusses two degree of freedom systems and provides equations of motion for a two degree of freedom spring-mass system with damping. It presents the matrix form of the equations of motion and defines the mass, damping and stiffness matrices. It then analyzes the free vibration of an undamped two degree of freedom system, determining the natural frequencies and normal modes of vibration. The normal modes allow expressing the motion as a superposition of the individual mode shapes.
Debabrata Pal, Aksum University, College of Engineering and Technology Department of Electrical and Computer Engineering Ethiopia, NE Africa, Email:debuoisi@gmail.com,website:www.ijrd.in
RedisDay London 2018 - CRDTs and Redis From sequential to concurrent executionsRedis Labs
CRDTs and Redis
- CRDTs (Conflict-Free Replicated Data Types) allow for data to be replicated across multiple systems and remain available even if those systems become disconnected from each other.
- Redis implements several CRDT data types including counters, registers, sets, and lists to provide causal consistency across replicas while preserving availability.
- The talk discusses how CRDTs transition from sequential execution models to concurrent ones while still preserving correctness and sequential semantics. Different concurrency policies, like add-wins and remove-wins sets, are explored.
This document contains 8 questions related to digital control systems for an examination. The questions cover various topics including:
1. Solving difference equations using Z-transforms
2. Obtaining state-space representations from transfer functions
3. Designing compensators to meet stability and performance specifications
4. Inverse Z-transforms and state-space modeling
5. Time and frequency response analysis of digital control systems
The questions require calculations, derivations and explanations related to foundational concepts in digital control systems.
This document describes research on developing parallel Monte Carlo algorithms for solving linear systems. It discusses using domain decomposition to parallelize Monte Carlo simulations across multiple processors. It presents methods for transporting random walks between domains and exiting transport loops without collective operations. Replication strategies are described to improve fault tolerance by running duplicate Monte Carlo simulations independently. Scaling studies show good strong and weak scaling on large supercomputers for problems with over 100 million unknowns.
This document provides an introduction and overview of MATLAB. It defines MATLAB as an interactive system for technical computing with matrices as the basic data type. It describes how MATLAB is used in mathematics, industry, and research for numeric computation and visualization. The document outlines MATLAB's toolboxes for specialized applications and provides examples of using matrices, vectors, operators, and functions in MATLAB. It demonstrates how to perform operations like matrix addition and inversion, solve systems of linear equations, and analyze arrays with built-in functions.
it is a lab manual, normally in various colleges filter designing is "Black-Sheep" on subjects. because many of the students failed in this exam.
it is very helpful to them.
this presentation will help u with understanding basic elements of the bloc diagram and how to reduce multi loop block diagram with some suitable numerical example.
Reduction of multiple subsystem [compatibility mode]azroyyazid
This document discusses techniques for reducing multiple subsystems to a single transfer function. It covers block diagram algebra and Manson's rule. Block diagram algebra can be used to reduce block diagrams representing cascaded, parallel, and feedback subsystems into equivalent single transfer functions. The key techniques are collapsing summing junctions and forming equivalent cascaded, parallel, and feedback systems. Signal-flow graphs also represent subsystems and can be reduced using Manson's rule by writing equations for each signal as the sum of incoming signals times their transfer functions. Examples demonstrate reducing various block diagrams and signal-flow graphs to equivalent single transfer functions.
The document describes the Newton-Raphson method for finding the roots of functions. It provides the derivation and algorithm for the method. An example problem is worked through, showing the estimates converging to a root over multiple iterations. Some potential drawbacks of the method are discussed, including divergence at inflection points, division by zero, oscillations near local extrema, and root jumping.
A block diagram uses blocks and lines to show the related functions of parts of an electric circuit or system. Such a diagram shows the normal order of progression of the signal through a circuit.
A system is an assembly of parts (components) connected together to perform a stated function.
The system may be comprises of:
• A number of individual components connected together
• A number of smaller units called subsystem.
o Each subsystem itself consists of individual parts
The document discusses frequency response and Bode plots. It begins by defining the sinusoidal transfer function and frequency response. The frequency response consists of the magnitude and phase functions of the transfer function. Bode plots graphically display the magnitude and phase functions versus frequency on logarithmic scales. The document then provides procedures for constructing Bode plots, including determining individual component responses, combining them, and reading off gain and phase margins. Examples are given to demonstrate the procedures.
This document discusses the time response of second order systems. It begins by defining key terms like natural frequency, damped frequency, and damping factor. It then analyzes the time response based on the value of the damping factor, categorizing systems as underdamped, undamped, critically damped, or overdamped. Underdamped systems oscillate with decaying amplitude, undamped systems oscillate without decay, critically damped systems decay exponentially without oscillation, and overdamped systems decay exponentially with two distinct time constants. Equations for the time response are derived for each case.
Computation of Electromagnetic Fields Scattered from Dielectric Objects of Un...Alexander Litvinenko
1) The document describes a method called Multilevel Monte Carlo (MLMC) to efficiently compute electromagnetic fields scattered from dielectric objects of uncertain shapes. MLMC balances statistical errors from random sampling and numerical errors from geometry discretization to reduce computational time.
2) A surface integral equation solver is used to model scattering from dielectric objects. Random geometries are generated by perturbing surfaces with random fields defined by spherical harmonics.
3) MLMC is shown to estimate scattering cross sections accurately while requiring fewer overall computations compared to traditional Monte Carlo methods. This is achieved by optimally allocating samples across discretization levels.
SIGNIFICANCE OF BLOCK DIAGRAM AND SIGNAL FLOW GRAPH IN CONTROL SYSTEMDinesh Sharma
This document discusses block diagrams and signal flow graphs, which are useful tools for modeling control systems. It begins by explaining what block diagrams are and how they represent the components and signal flows in a system. Signal flow graphs are then introduced as a more compact way to determine the relationships between input and output variables using Mason's gain formula, without needing to reduce the diagram. The document provides examples of block diagram reductions and simple signal flow graphs. It concludes that block diagrams and signal flow graphs provide control engineers a better understanding of systems by describing the connections between components.
This document discusses block diagram representation. It begins by defining a block diagram as a pictorial representation of the cause-and-effect relationship of a system. Block diagrams show the components, direction of information flow with arrows, and can describe the function of each block. Block diagrams are useful for analyzing and designing control systems, but do not provide unique representations or show the physical construction or energy sources of a system. The document also discusses techniques for reducing block diagrams, such as combining or moving blocks.
This document provides information about a Control Systems Theory course, including:
- The assessment breakdown is 20% mini project, 20% lab report, 20% test, and 40% final exam.
- The teaching plan covers topics like system representation, response analysis, stability analysis, and controller design over 14 weeks.
- The objectives are to understand control systems concepts and evaluate system responses.
- Control systems are used to amplify power, allow remote control, improve input/output forms, and compensate for disturbances. Examples given include elevators, cruise control, ABS, and vehicle suspension.
On the principle of optimality for linear stochastic dynamic systemijfcstjournal
In this work, processes represented by linear stochastic dynamic system are investigated and by
considering optimal control problem, principle of optimality is proven. Also, for existence of optimal
control and corresponding optimal trajectory, proofs of theorems of necessity and sufficiency condition are
attained.
Multiple Sensors Soft-Failure Diagnosis Based on Kalman Filtersipij
Sensor is the necessary components of the engine control system. Therefore, more and more work must do for improving sensors reliability. Soft failures are small bias errors or drift errors that accumulate relatively slowly with time in the sensed values that it must be detected because of it can be very easy to be mistaken for the results of noise. Simultaneous multiple sensors failures are rare events and must be considered. In order to solve this problem, a revised multiple-failure-hypothesis based testing is investigated. This approach uses multiple Kalman filters, and each of Kalman filter is designed based on a specific hypothesis for detecting specific sensors fault, and then uses Weighted Sum of Squared Residual (WSSR) to deal with Kalman filter residuals, and residual signals are compared with threshold in order to make fault detection decisions. The simulation results show that the proposed method can be used to detect multiple sensors soft failures fast and accurately.
Introduction to Convolutional Codes
Convolutional Encoder Structure
Convolutional Encoder Representation(Vector, Polynomial, State Diagram and Trellis Representations )
Maximum Likelihood Decoder
Viterbi Algorithm
MATLAB Simulation
Hard and Soft Decisions
Bit Error Rate Tradeoff
Consumed Time Tradeoff
This document discusses two degree of freedom systems and provides equations of motion for a two degree of freedom spring-mass system with damping. It presents the matrix form of the equations of motion and defines the mass, damping and stiffness matrices. It then analyzes the free vibration of an undamped two degree of freedom system, determining the natural frequencies and normal modes of vibration. The normal modes allow expressing the motion as a superposition of the individual mode shapes.
Debabrata Pal, Aksum University, College of Engineering and Technology Department of Electrical and Computer Engineering Ethiopia, NE Africa, Email:debuoisi@gmail.com,website:www.ijrd.in
RedisDay London 2018 - CRDTs and Redis From sequential to concurrent executionsRedis Labs
CRDTs and Redis
- CRDTs (Conflict-Free Replicated Data Types) allow for data to be replicated across multiple systems and remain available even if those systems become disconnected from each other.
- Redis implements several CRDT data types including counters, registers, sets, and lists to provide causal consistency across replicas while preserving availability.
- The talk discusses how CRDTs transition from sequential execution models to concurrent ones while still preserving correctness and sequential semantics. Different concurrency policies, like add-wins and remove-wins sets, are explored.
This document contains 8 questions related to digital control systems for an examination. The questions cover various topics including:
1. Solving difference equations using Z-transforms
2. Obtaining state-space representations from transfer functions
3. Designing compensators to meet stability and performance specifications
4. Inverse Z-transforms and state-space modeling
5. Time and frequency response analysis of digital control systems
The questions require calculations, derivations and explanations related to foundational concepts in digital control systems.
This document describes research on developing parallel Monte Carlo algorithms for solving linear systems. It discusses using domain decomposition to parallelize Monte Carlo simulations across multiple processors. It presents methods for transporting random walks between domains and exiting transport loops without collective operations. Replication strategies are described to improve fault tolerance by running duplicate Monte Carlo simulations independently. Scaling studies show good strong and weak scaling on large supercomputers for problems with over 100 million unknowns.
This document provides an introduction and overview of MATLAB. It defines MATLAB as an interactive system for technical computing with matrices as the basic data type. It describes how MATLAB is used in mathematics, industry, and research for numeric computation and visualization. The document outlines MATLAB's toolboxes for specialized applications and provides examples of using matrices, vectors, operators, and functions in MATLAB. It demonstrates how to perform operations like matrix addition and inversion, solve systems of linear equations, and analyze arrays with built-in functions.
This document summarizes a study on sliding mode control of a permanent magnet synchronous machine (PMSM). The study models the PMSM and voltage inverter, applies field oriented control to decouple the system, then designs a sliding mode controller. The controller uses a sliding surface and switching control law to make the system robust to uncertainties. Simulation results showed the controller improved robustness and solved the chattering problem of prior sliding mode controllers for PMSM.
Hybrid Fuzzy Sliding Mode Controller for Timedelay Systemijaia
This document describes a hybrid fuzzy sliding mode controller for time-delay systems. It begins by introducing time-delay systems and discussing sliding mode control as a suitable technique. It then presents the design of a sliding surface for the error function of a nonlinear time-delay system. Next, it describes constructing a fuzzy logic controller by designing a fuzzy rule base using the generated error signals. Simulation results found the proposed scheme to be robust even with perturbed system parameters. The aim is to develop an effective control algorithm for highly unstable nonlinear systems such as aerospace systems.
Platoon Control of Nonholonomic Robots using Quintic Bezier SplinesKaustav Mondal
In this project, quintic polynomials were used to perform platooning in nonholonomic robots. Both hardware and simulations results have been presented.
On the State Observer Based Stabilization of T-S Systems with Maximum Converg...CSCJournals
This paper presents improved relaxed stabilization conditions and design procedures of state observers based controllers for continuous nonlinear systems in T-S model representation. First, the T-S model approach for nonlinear systems and some stabilization results are recalled. New stabilization conditions are obtained by relaxing those derived in previous works in this field. The asymptotic and exponential stabilization are considered with the maximization of the convergence rate. A design procedure for stabilizing T-S observer based controller using the concept of PDC (Parallel Distributed Compensation) and the improved relaxed stabilization conditions is proposed.
This document discusses fault analysis in power systems. It begins with an overview of fault types and causes, including lightning strikes. Transmission line faults are modeled using RL circuits to determine fault currents. Generators contribute the majority of fault current and are modeled using reactances valid for different time periods. Network faults are simplified by modeling lines as reactances and transformers as leakage reactances. An example network fault is solved using the superposition method to find the fault current.
This document summarizes algorithms for solving the lowest common ancestor (LCA) problem and range minimum query (RMQ) problem in trees. It presents a reduction from LCA to RMQ that allows solving LCA in O(n) time using an O(n) time RMQ algorithm. It describes several RMQ algorithms, including a naive O(n^3) time algorithm, an O(n^2) dynamic programming algorithm, and an O(n log n) sparse table algorithm. For the special case where the values in the array differ by at most 1, it presents an O(n) time and O(1) time RMQ algorithm based on partitioning the array into blocks.
DSP_2018_FOEHU - Lec 03 - Discrete-Time Signals and SystemsAmr E. Mohamed
The document discusses discrete-time signals and systems. It defines discrete-time signals as sequences represented by x[n] and discusses important sequences like the unit sample, unit step, and periodic sequences. It then defines discrete-time systems as devices that take a discrete-time signal x(n) as input and produce another discrete-time signal y(n) as output. The document classifies systems as static vs. dynamic, time-invariant vs. time-varying, linear vs. nonlinear, and causal vs. noncausal. It provides examples to illustrate each classification.
Introduction to Information Technology Lecture 2MikeCrea
Number Systems
Types of number systems
Number bases
Range of possible numbers
Conversion between number bases
Common powers
Arithmetic in different number bases
Shifting a number
This document defines and describes dynamical systems. It begins by defining a dynamical system as a system that changes over time according to fixed rules determining how its states change. It then describes the two main parts of a dynamical system: (1) a state vector describing the system's current state, and (2) a function determining the next state. Dynamical systems can be classified as linear/nonlinear, autonomous/nonautonomous, conservative/nonconservative, discrete/continuous, and one-dimensional/multidimensional. The document provides examples of classifying systems and calculating eigenvalues and eigenvectors. It discusses how diagonalizing a matrix simplifies solving dynamical systems.
2014 spring crunch seminar (SDE/levy/fractional/spectral method)Zheng Mengdi
This document summarizes numerical methods for simulating stochastic partial differential equations (SPDEs) with tempered alpha-stable (TαS) processes. It discusses two main methods:
1) The compound Poisson (CP) approximation method, which simulates large jumps as a CP process and replaces small jumps with their expected drift term.
2) The series representation method, which represents the TαS process as an infinite series involving i.i.d. random variables.
It also provides algorithms for implementing these two methods and applies them to simulate specific examples like reaction-diffusion equations with TαS noise. Numerical results demonstrate that both methods can accurately capture the statistics of the underlying TαS
Fault modeling and parametric fault detection in analog VLSI circuits using d...IJECEIAES
In this article we describe new model for determination of fault in circuit and also we provide detailed analysis of tolerance of circuit, which is considered one of the important parameter while designing the circuit. We have done mathematical analysis to provide strong base for our model and also done simulation for the same. This article describes detailed analysis of parametric fault in analog VLSI circuit. The model is tested for different frequencies for compactness and its flexibility. The tolerance analysis is also done for this purpose. All the simulation are done in MATLAB software.
Discussed different types of dynamic interconnection networks. Graphically demonstrated single and multiple bus interconnection networks. Discussed different types of switch based interconnection networks. Graphically shown the mechanisms of crossbar, single and multistage interconnection networks. Graphically explained the working principle of omega network, Benes network, and baseline networks.
Machine Learning in Agriculture Module 6: classificationPrasenjit Dey
Define the classification problem. Discuss different performance evaluation metrics in classification problem, Graphically demonstrate the concepts of true positive, true negative, false positive, false negative, sensitivity and specificity, confusion matrix, precision and recall, Concepts of ROC and AUC curve
Machine Learning in Agriculture Module 3: linear regressionPrasenjit Dey
This document discusses using machine learning for agriculture applications. It introduces linear regression, including definitions and measurements like mean absolute error, mean squared error, and R2 metric. It then demonstrates how to use Google Colab notebooks and Python code to perform linear regression on crop yield data. Code examples are provided for loading and preparing data, fitting a linear regression model, making predictions, and calculating error metrics. Cross-validation is also demonstrated to evaluate model performance.
Machine Learning in Agriculture Module 1Prasenjit Dey
Discuss the opportunities of incorporation of machine learning in agriculture. Briefly discuss different machine learning strategies. Briefly discuss the ways of machine learning can be used
The document discusses support vector machines (SVMs). SVMs find the optimal separating hyperplane between classes that maximizes the margin between them. They can handle nonlinear data using kernels to map the data into higher dimensions where a linear separator may exist. Key aspects include defining the maximum margin hyperplane, using regularization and slack variables to deal with misclassified examples, and kernels which implicitly map data into other feature spaces without explicitly computing the transformations. The regularization and gamma parameters affect model complexity, with regularization controlling overfitting and gamma influencing the similarity between points.
Explained response time and CPU time, difference between them, Explained clock cycle time, clock frequency, clock rate, cycle per instruction(CPI), million instruction per second(MIPS), etc. Describe Amdahl's law with numerical examples
Defined instruction set architecture, discussed different types of instructions in the MIPS architecture, e.g., arithmetic, logical, shift etc. Discussed different types of registers in MIPS, R-format, I-format and j-format instructions have been explained with examples. Further assembly language code for conditional operations e.g., if..else, swap operation, loop operation are demonstrated.
The document discusses different addressing modes used in instruction sets. It describes inherent, immediate, direct, indirect, register, register indirect, displacement, relative, indexed, auto-increment/decrement, and stack addressing modes. Each addressing mode specifies how the effective address of an operand is represented in an instruction. Different addressing modes are used for different types of instructions depending on factors like speed of access and address space.
Register transfer and microoperations part 2Prasenjit Dey
The document discusses various types of microoperations including register transfer, arithmetic, logic, and shift microoperations. It provides details on how basic arithmetic operations like addition, subtraction, and increment/decrement are implemented. Logic operations like AND, OR, XOR, and NOT are also covered. Shift operations include logical, circular, and arithmetic shifts. The hardware implementation of these microoperations uses basic logic gates and circuits like half adders, full adders, and multiplexers.
The document discusses instruction sets and their components. It defines an instruction set as the list of instructions available for the CPU, which are encoded in binary machine language or assembly language mnemonics. Each instruction contains an operation code and may include source and destination operand references. Instruction formats can vary in the number of operands from zero to three addresses. Instruction length, encoding techniques, and types of instructions like data transfer, arithmetic, and control instructions are also covered.
Register transfer and microoperations part 1Prasenjit Dey
Register transfer language, hardware implementation of bus transfer using multiplexer and three state buffer, hardware implementation of memory transfer e.g., memory read and memory write.
Different types of memory and hardware designs of RAM and ROMPrasenjit Dey
Discussed the memory hierarchy, the characteristics of memory like location, unit of data transfer, access method, and performance. Then demonstrate the design of both RAM and ROM chip. Shows how to configure the memory unit composed of both RAM and ROM using multiple RAM and ROM chips i n hardware. Finally, demonstrate the design of the magnetic disks
Explain cache memory with a diagram, demonstrate hit ratio and miss penalty with an example. Discussed different types of cache mapping: direct mapping, fully-associative mapping and set-associative mapping. Discussed temporal and spatial locality of references in cache memory. Explained cache write policies: write through and write back. Shown the differences between unified cache and split cache.
Explain the drawbacks of Ripple carry adder, then derives the expression of Carry look ahead adder from Full Adder. After that, demonstrated the generalized expression of Carry look ahead adder. Finally, shows the hardware architecture of a Carry look ahead adder.
The document describes two methods for multiplying two binary numbers. Method 1 uses shifting and addition. Method 2 improves on Method 1 by using an additional carry bit and not modifying the multiplicand during iterations. The document also describes Booth's multiplication algorithm which determines arithmetic actions based on pairs of bits in the multiplier and handles signed numbers. An example of multiplying -5x14 is shown step-by-step using Booth's algorithm.
Computer organization basics and number systemsPrasenjit Dey
Discussed the basics of a computer, e.g., CPU, ALU, CU, different types of memory, instruction cycle. Then, different number systems like binary, gray, excess-3 has been explored. Finally, binary arithmetic has been explain by one's & two's complement.
How to Fix the Import Error in the Odoo 17Celine George
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.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
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.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
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.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
4. Collision free scheduling
To avoid collisions, all tasks should be scheduled properly
The objective is to achieve shortest average latency
between initiations without causing collisions
Steps to achieve shortest average latency are
Computation of collision vector
Formation of State diagram
Computation of greedy cycles
Computation of Minimum Average Latency (MAL)
5. Collision Vectors
A vector of m-bits, where m is Max(forbidden latency)
Length of collision vector = maximum forbidden latency = 7
The bit position (Bi)= 1 if latency i causes collision
The bit position (Bi)= 0 if latency i do not cause collision
Collision vector is = (cm,cm-1, …, c2, c1) = 1011010
This is the Initial Collision Vector (ICV)
1 2 3 4 5 6 7 8
S1 X1 X1 x1
S2 X1 x1
S3 X1 X1 X1
6. State Diagrams
A state diagram is formed from the collision vector
It shows are permissible state transitions among successive
initiations
Right shift ICV, then OR it with ICV
1011010
1011011 1111111
8+
3 6 8+ 1* 8+
3* 6
1011010 >>1
0101101
0101101
OR
1011010
1111111
7. Greedy Cycles
Simple cycles: a latency cycle in which each state appears only
once
Greedy cycles: Is a simple cycle whose edges are all made with
minimum latencies from their respective starting states
Their average latencies must be lower than those of other simple
cycles
Simple cycles were (1,8),(3,6),(6,8)(8)(3),(6)
Greedy cycles = (3),(1,8)
Average Latency(3)=3
Average Latency(1,8)=4.5
MAL (Minimum Average Latency)= 3
8. Schedule Optimization
As greedy cycle not sufficient for optimality of MAL, lower
bound on MAL is required
Optimize the reservation table to obtain the lower bound