Unsupervised Signal Processing
eBook - PDF

Unsupervised Signal Processing

Channel Equalization and Source Separation

  1. 340 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Unsupervised Signal Processing

Channel Equalization and Source Separation

About this book

Unsupervised Signal Processing: Channel Equalization and Source Separation provides a unified, systematic, and synthetic presentation of the theory of unsupervised signal processing. Always maintaining the focus on a signal processing-oriented approach, this book describes how the subject has evolved and assumed a wider scope that covers several topics, from well-established blind equalization and source separation methods to novel approaches based on machine learning and bio-inspired algorithms.

From the foundations of statistical and adaptive signal processing, the authors explore and elaborate on emerging tools, such as machine learning-based solutions and bio-inspired methods. With a fresh take on this exciting area of study, this book:



  • Provides a solid background on the statistical characterization of signals and systems and on linear filtering theory
  • Emphasizes the link between supervised and unsupervised processing from the perspective of linear prediction and constrained filtering theory
  • Addresses key issues concerning equilibrium solutions and equivalence relationships in the context of unsupervised equalization criteria
  • Provides a systematic presentation of source separation and independent component analysis
  • Discusses some instigating connections between the filtering problem and computational intelligence approaches.

Building on more than a decade of the authors' work at DSPCom laboratory, this book applies a fresh conceptual treatment and mathematical formalism to important existing topics. The result is perhaps the first unified presentation of unsupervised signal processing techniques—one that addresses areas including digital filters, adaptive methods, and statistical signal processing. With its remarkable synthesis of the field, this book provides a new vision to stimulate progress and contribute to the advent of more useful, efficient, and friendly intelligent systems.

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Yes, you can access Unsupervised Signal Processing by João Marcos Travassos Romano,Romis Attux,Charles Casimiro Cavalcante,Ricardo Suyama in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Networking. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Front cover
  2. Contents
  3. List of Figures
  4. List of Tables
  5. Foreword
  6. Preface
  7. Acknowledgments
  8. Authors
  9. Chapter 1: Introduction
  10. Chapter 2: Statistical Characterization of Signals and Systems
  11. Chapter 3: Linear Optimal and Adaptive Filtering
  12. Chapter 4: Unsupervised Channel Equalization
  13. Chapter 5: Unsupervised Multichannel Equalization
  14. Chapter 6: Blind Source Separation
  15. Chapter 7: Nonlinear Filtering and Machine Learning
  16. Chapter 8: Bio-Inspired Optimization Methods
  17. Appendix A: Some Properties of the Correlation Matrix
  18. Appendix B: Kalman Filter
  19. References
  20. Back cover