Description

This third volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in array and statistical signal processing.

With this reference source you will:

  • Quickly grasp a new area of research 
  • Understand the underlying principles of a topic and its application
  • Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved

Key Features

  • Quick tutorial reviews of important and emerging topics of research in array and statistical signal processing
  • Presents core principles and shows their application
  • Reference content on core principles, technologies, algorithms and applications
  • Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge
  • Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic

Readership

R&D engineers in signal processing and wireless and mobile communications

Table of Contents

Introduction

Signal Processing at Your Fingertips!

About the Editors

Section Editors

Section 1

Section 2

Authors Biography

Section 1: Statistical Signal Processing

Chapter 1. Introduction to Statistical Signal Processing

Acknowledgments

3.01.1 A brief historical recount

3.01.2 Content

3.01.3 Contributions

3.01.4 Suggested further reading

References

Chapter 2. Model Order Selection

Abstract

3.02.1 Introduction

3.02.2 Example: variable selection in regression

3.02.3 Methods based on statistical inference paradigms

3.02.4 Information and coding theory based methods

3.02.5 Example: estimating number of signals in subspace methods

3.02.6 Conclusion

References

Chapter 3. Non-Stationary Signal Analysis Time-Frequency Approach

Abstract

3.03.1 Introduction

3.03.2 Linear signal transforms

3.03.3 Quadratic time-frequency distributions

3.03.4 Higher order time-frequency representations

3.03.5 Processing of sparse signals in time-frequency

3.03.6 Examples of time-frequency analysis applications

References

Chapter 4. Bayesian Computational Methods in Signal Processing

Abstract

3.04.1 Introduction

3.04.2 Parameter estimation

3.04.3 Computational methods

3.04.4 State-space models and sequential inference

3.04.5 Conclusion

A Probability densities and integrals

References

Chapter 5. Distributed Signal Detection

Abstract

3.05.1 Introduction

3.05.2 Distributed detection with independent observations

3.05.3 Distributed detection with dependent observations

3.05.4 Conclusion

References

Chapter 6. Quickest Change Detection

Abstract

Acknowledgments

3.06.1 Introduction

3.

Details

No. of pages:
1012
Language:
English
Copyright:
© 2014
Published:
Imprint:
Academic Press
Print ISBN:
9780124115972
Electronic ISBN:
9780124116214