This book studies the link between differential beamforming and differential equations which in turn enables the study of fundamental theory and methods of beamforming from a different perspective, leading to new insights into the problem and new methods to solve the problem. The book first presents
Array Beamforming with Linear Difference Equations: 20 (Springer Topics in Signal Processing, 20)
β Scribed by Jacob Benesty, Israel Cohen, Jingdong Chen
- Publisher
- Springer
- Year
- 2021
- Tongue
- English
- Leaves
- 175
- Edition
- 1st ed. 2021
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book studies the link between differential beamforming and differential equations which in turn enables the study of fundamental theory and methods of beamforming from a different perspective, leading to new insights into the problem and new methods to solve the problem. The book first presents a brief overview of the problems and methods for beamforming and some performance measures popularly used either to evaluate beamformers or to derive optimal beamformers. Then, first-order, second-order, and general high-order linear difference equations are discussed, based on which the authors show how to formulate the beamforming problem and derive different beamforming methods, including fixed and adaptive ones. Furthermore, the authors show how to apply the theory of difference equations to the general problem of speech enhancement, and deduce a number of noise reduction filters, including the maximum SNR filter, the Wiener filter, the MVDR filter, etc. Also covered in the book are the difference equations and differential beamforming from the spectral graph perspective.
- Presents basic concepts, fundamental principles, and methods for beamforming from the perspective of linear difference equations;
- Provides formulation and methods of conventional beamforming, and first-order, second-order, and general high-order linear difference equations for beamforming;
- Includes the applications of linear difference equations to the problem of noise reduction;
- Explains beamforming based on difference equations with graphs.
β¦ Table of Contents
Abstract
Contents
1 Introduction
1.1 Beamforming and Noise Reduction
1.2 Organization of the Work
References
2 A Brief Overview of Conventional Beamforming
2.1 Signal Model
2.2 Linear Beamforming
2.3 Performance Measures
2.4 Examples of Optimal Beamformers
References
3 Beamforming with First-Order Linear Difference Equations
3.1 Signal Model
3.2 First-Order Linear Difference Beamforming
3.3 Performance Measures
3.4 Examples of Optimal Fixed Beamformers
3.5 Examples of Optimal Adaptive Beamformers
References
4 Beamforming with Second-Order Linear Difference Equations
4.1 Signal Model
4.2 Second-Order Linear Difference Beamforming
4.3 Performance Measures
4.4 Examples of Optimal Fixed Beamformers
4.5 Examples of Optimal Adaptive Beamformers
References
5 Beamforming with Higher-Order Linear Difference Equations
5.1 Signal Model
5.2 Higher-Order Linear Difference Beamforming
5.3 Performance Measures
5.4 Examples of Optimal Fixed Beamformers
5.5 Examples of Optimal Adaptive Beamformers
References
6 Application to Speech Enhancement
6.1 Signal Model
6.2 Linear Difference Filtering
6.3 Performance Measures
6.4 Examples of Optimal Speech Enhancement Filters
References
7 A Spectral Graph Perspective
7.1 Mathematical Background
7.2 Beamforming with Linear Difference Equations on Graphs
References
Index
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