Sampling in Digital Signal Processing and Control

Undoubtably one of the key factors influencing recent technology has been the advent of high speed computational tools. Virtually every advanced engi­ neering system we come in contact with these days depends upon some form of sampling and digital signal processing. Well known examples are digital t...

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Main Authors: Feuer, Arie, Goodwin, Graham (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Boston, MA Birkhäuser Boston 1996, 1996
Edition:1st ed. 1996
Series:Systems & Control: Foundations & Applications
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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100 1 |a Feuer, Arie 
245 0 0 |a Sampling in Digital Signal Processing and Control  |h Elektronische Ressource  |c by Arie Feuer, Graham Goodwin 
250 |a 1st ed. 1996 
260 |a Boston, MA  |b Birkhäuser Boston  |c 1996, 1996 
300 |a XXXII, 544 p  |b online resource 
505 0 |a A Time Domain Perspective -- 10.3 Other Applications of Generalized Sample-Hold Functions -- 10.4 Frequency Domain Analysis of GSHF -- 10.5 Sensitivity Considerations -- 10.6 Further Reading and Discussion --  
505 0 |a 10.7 Problems -- 11 Periodic Control of Linear Time-Invariant Systems -- 11.1 Introduction -- 11.2 Periodic Control of Linear Time-Invariant Systems -- 11.3 Time Domain Analysis -- 11.4 Frequency Domain Analysis -- 11.5 Further Reading and Discussion -- 11.6 Problems -- 12 Multirate Control -- 12.1 Introduction -- 12.2 A Unifying Approach -- 12.3 Slow Output Sampling, Fast Input Sampling -- 12.4 Fast Output Sampling, Slow Input Sampling -- 12.5 Further Reading and Discussion -- 12.6 Problems -- 13 Optimal Control of Periodic Systems -- 13.1 Introduction -- 13.2 Control of Linear Periodic Systems -- 13.3 Control based on State Estimate Feedback -- 13.4 Further Reading and Discussion -- 13.5 Problems 
505 0 |a 5.7 Further Reading and Discussion -- 5.8 Problems -- 6 Optimal Linear Estimation with State-Space Filters -- 6.1 Introduction -- 6.2 Signal Model -- 6.3 The Sampling Process -- 6.4 Discrete Stochastic Model -- 6.5 The Discrete Kalman Filter -- 6.6 Continuous-Time State Estimation -- 6.7 Further Reading and Discussion -- 6.8 Problems -- 7 Periodic and Multirate Filtering -- 7.1 Introduction -- 7.2 Models for Periodic Linear Systems -- 7.3 The Raising Procedure -- 7.4 Frequency Domain Analysis of Periodic Filters -- 7.5 Models for Sampled Periodic Stochastic Systems -- 7.6 Periodic Optimal Filtering -- 7.7 Further Reading and Discussion -- 7.8 Problems -- 8 Discrete-Time Control -- 8.1 Introduction -- 8.2 Closed-Loop Stability and Pole Assignment -- 8.3 Some Special Discrete-Time Control Laws -- 8.4 Sensitivity and Complementary Sensitivity Functions -- 8.5 All Stabilizing Control Laws -- 8.6 State Estimate Feedback --  
505 0 |a 1 Fourier Analysis -- 1.1 Introduction -- 1.2 The Basic Transforms -- 1.3 Properties of Continuous-Time Fourier Transforms -- 1.4 Properties of Discrete-Time Fourier Transforms -- 1.5 The ? — Impulse Stream -- 1.6 Inter-relating the Various Transforms -- 1.7 Special Topics -- 1.8 Further Reading and Discussion -- 1.9 Problems -- 2 Sampling and Reconstruction -- 2.1 Introduction -- 2.2 Sampled Data Sequences — A Representation of Continuous Signals -- 2.3 Continuous Signal Reconstruction from a Sampled Data Sequence -- 2.4 Shannon’ s Reconstruction Theorem -- 2.5 Practical Methods of Reconstruction -- 2.6 Signal Reconstruction from Periodic Samples -- 2.7 Further Reading and Discussion -- 2.8 Problems -- 3 Analysis of Discrete-Time Systems -- 3.1 Introduction -- 3.2 Shift Operator Models -- 3.3 z-Transforms -- 3.4 The Delta Operator -- 3.5 Difference Equations in Delta Operator Form -- 3.6 Discrete Delta Transform --  
505 0 |a 3.7 Use of Discrete Delta Transforms to Solve Difference Equations -- 3.8 The Discrete Transfer Function -- 3.9 Summary of Delta Transform Properties -- 3.10 Stability of Discrete Systems -- 3.11 Discrete Frequency Response -- 3.12 Frequency Domain Stability Criteria for Discrete-Time Systems -- 3.13 Digital Filter Implementation -- 3.14 Further Reading and Discussion -- 3.15 Problems -- 4 Discrete-Time Models of Continuous Deterministic Systems -- 4.1 Introduction -- 4.2 State-Space Development -- 4.3 Transform Development -- 4.4 Continuous-Time and Discrete-Time Poles and Zeros -- 4.5 Numerical Issues -- 4.6 Frequency Domain Development -- 4.7 Further Reading and Discussion -- 4.8 Problems -- 5 Optimal Linear Estimation with Finite Impulse Response Filters -- 5.1 Introduction -- 5.2 Problem Description -- 5.3 Sampled Model -- 5.4 The Discrete Lattice Filter -- 5.5 Continuous-Time Lattice Structure -- 5.6 Relationships between the Discrete and Continuous Lattice Filters --  
653 |a Computational Mathematics and Numerical Analysis 
653 |a Mathematics, general 
653 |a Image processing 
653 |a Signal, Image and Speech Processing 
653 |a Speech processing systems 
653 |a Computer mathematics 
653 |a Signal processing 
653 |a Mathematics 
700 1 |a Goodwin, Graham  |e [author] 
710 2 |a SpringerLink (Online service) 
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490 0 |a Systems & Control: Foundations & Applications 
856 |u https://doi.org/10.1007/978-1-4612-2460-0?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 621.382 
520 |a Undoubtably one of the key factors influencing recent technology has been the advent of high speed computational tools. Virtually every advanced engi­ neering system we come in contact with these days depends upon some form of sampling and digital signal processing. Well known examples are digital tele­ phone systems, digital recording of audio signals and computer control. These developments have been matched by the appearance of a plethora of books which explain a variety of analysis, synthesis and design tools applica­ ble to sampled-data systems. The reader might therefore wonder what is distinc­ tive about the current book. Our observation of the existing literature is that the underlying continuous-time system is usually forgotten once the samples are tak­ en. The alternative point of view, adopted in this book, is to formulate the analy­ sis in such a way that the user is constantly reminded of the presence of the under­ lying continuous-time signals. We thus give emphasis to two aspects of sampled-data analysis: Firstly, we formulate the various algorithms so that the appropriate contin­ uous-time case is approached as the sampling rate increases. Secondly we place emphasis on the continuous-time output response rath­ er than simply focusing on the sampled response