Applied and Computational Control, Signals, and Circuits

Applied and Computational Control, Signals, and Circuits
By:"Biswa N. Datta"
Published on 1999-07-28 by Springer Science & Business Media

E-book Library:"Computers"

As the first volume in a new annual survey , Applied and Computational Control, Signals, and Circuits is an interdisciplinary publication which provides surveys, expository papers, algorithms, and software reviews. These volumes address significant new developments, applications, and computational methods in control, signal processing, circuit design and analysis. The goal is to provide authoritative and accessible accounts of the rapid development in computational engineering methods, applications, and algorithms. Each volume contains surveys and chapters representing a balance of coverage from the major areas of control, signals, and circuits. The contributions, selected by an editorial board comprised of leading researchers, contain all necessary background information and are extensive presentations of the topics. Topics and Features: Control, filtering, and systems identification Signal and image processing Circuit simulation Linear-control-systems software library, SLICOT Array algorithms Researchers, practitioners, and professionals in computer science, scientific computing, and engineering will find the volume essential for keeping abreast of the latest developments and for critically assessing new software tools. Table of Contents Chapter 1 Discrete Event Systems: The State of the Art and New Directions 1.1 Introduction 1.2 ES Modeling Framework 1.3 Review of the State of the Art in DES Theory 1.4 New Directions in DES Theory 1.5 Decentralized Control and Optimization 1.6 Failure Diagnosis 1.7 Nondeterministic Supervisory Control 1.8 Hybrid Systems and Optimal Control Chapter 2 Array Algorithms for H2 and H-Infinity Estimation 2.1 Introduction 2.2 H2 Square-Root Array Algorithms 2.3 H-Infinity Square-Root Array Algorithms 2.4 H2 Fast Array Algorithms 2.5 H-Infinity Fast Array Algorithms 2.6 Conclusion 2.A Unitary and Hyperbolic Rotations 2.B Krein Spaces Chapter 3 Non-uniqueness, Uncertainty and Complexity in Modeling 3.1 Introduction 3.2 Issues of Models and Modeling 3.3 Non-Uniqueness 3.4 Uncertainty 3.5 Complexity 3.6 Formulation of Model Set Identification 3.7 Learning or Optimization? 3.8 Conclusion Chapter 4 Iterative Learning Control - An Expository Overview 4.1 Introduction 4.2 Generic Description of ILC 4.3 Two Illustrative Examples of ILC Algorithms 4.4 The Literature, Context, Terminology of ILC 4.5 ILC Algorithms and Results 4.6 Example: Combining Some New ILC Approaches 4.7 Conclusion: The Past, Present, and Future of ILC Chapter 5 FIR Filter Design via Spectral Factorization and Convex Optimization 5.1 Introduction 5.2 Spectral factorization 5.3 Convex semi-infinite optimization 5.4 Lowpass filter design 5.5 Log-Chebychev approximation 5.6 Magnitude equalizer design 5.7 Linear antenna array weight design 5.8 Conclusions 5.A Appendix Chapter 6 Algorithms for Subspace State Space System Identification - An Overview 6.1 System identification: To measure is to know! 6.2 Linear subspace identification: an overview 6.3 Comparing PEM with subspace methods 6.4 Statistical consistency results 6.5 Extensions Chapter 7 Iterative Solution Methods for Large Linear Discrete Illposed Problems 7.1 Introduction 7.2 Krylov subspace iterative methods 7.3 Tikhonov regulariztion 7.4 An exponential filter function 7.5 Iterative methods based on implicitly defined filter functions 7.6 Towards a black box 7.7 Computed examples Chapter 8 Wavelet-Based Image Coding: An Overview 8.1 Introduction 8.2 Quantization 8.3 Transform Coding 8.4 Wavelets: A Different Perspective 8.5 A Basic Wavelet Image Coder 8.6 Extending the Transform Coder Paradigm 8.7 Zerotree Coding 8.8 Frequency, space-frequency adaptive coders 8.9 Utilizing Intra-band Dependencies 8.10 Future Trends 8.11 Summary and Conclusion Chapter 9 Reduced-Order Modeling Techniques Based on Krylov Subspaces and their Use in Circuit Simulation 9.1 Introduction 9.2 Reduced-Order Modeling of Linear Dynamical Systems 9.3 Linear Systems in Circuit Simulation 9.4 Krylov Subspaces and Moment Modeling 9.5 The Lanczos Process 9.6 Lanczos-Based Reduced-Order Modeling 9.7 The Arnoldi Process 9.8 Arnoldi-Based Reduced-Order Modeling 9.9 Circuit-Noise Computations 9.10 Concluding Remarks Chapter 10 SLICOT - A Subroutine Library in Systems and Control Theory 10.1 Introduction 10.2 Why Do We Need More Than MATLAB Numerics? 10.3 Retrospect 10.4 The Design of SLICOT 10.5 Contents of SLICOT 10.6 Performance Results 10.7 The Future - NICONET 10.8 Concluding Remarks 10.A Contents of SLICOT Release 3.0 10.B Electronic Access to the Library and Related Literature

This Book was ranked 7 by Google Books for keyword vectorwise.

Thank you
E-Book University