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E-raamat: Signal Enhancement with Variable Span Linear Filters

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This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.
1 Introduction
1(6)
1.1 Signal Enhancement from a Signal Subspace Perspective
2(1)
1.2 From Subspace Methods to Variable Span Linear Filters
3(1)
1.3 Organization of the Work
4(3)
References
5(2)
2 General Concept with Filtering Vectors
7(18)
2.1 Signal Model and Problem Formulation
7(1)
2.2 Joint Diagonalization
8(1)
2.3 Variable Span (VS) Linear Filtering
9(2)
2.4 Performance Measures
11(3)
2.4.1 Noise Reduction
11(1)
2.4.2 Desired Signal Distortion
12(1)
2.4.3 Mean-Squared Error (MSE) Criterion
13(1)
2.5 Optimal VS Linear Filters
14(4)
2.5.1 VS Minimum Distortion
14(2)
2.5.2 VS Wiener
16(1)
2.5.3 VS Tradeoff
17(1)
2.6 Indirect Optimal VS Linear Filters
18(7)
2.6.1 Indirect Approach
18(2)
2.6.2 MSE Criterion and Performance Measures
20(1)
2.6.3 Optimal Filters
21(3)
References
24(1)
3 General Concept with Filtering Matrices
25(16)
3.1 Signal Model and Problem Formulation
25(1)
3.2 VS Linear Filtering with a Matrix
25(2)
3.3 Performance Measures
27(3)
3.3.1 Noise Reduction
27(1)
3.3.2 Desired Signal Distortion
28(1)
3.3.3 MSE Criterion
29(1)
3.4 Optimal VS Linear Filtering Matrices
30(4)
3.4.1 VS Minimum Distortion
30(2)
3.4.2 VS Wiener
32(1)
3.4.3 VS Tradeoff
33(1)
3.5 Indirect Optimal VS Linear Filtering Matrices
34(7)
3.5.1 Indirect Approach
34(1)
3.5.2 MSE Criterion and Performance Measures
35(2)
3.5.3 Optimal Filtering Matrices
37(2)
References
39(2)
4 Single-Channel Signal Enhancement in the STFT Domain
41(34)
4.1 Signal Model and Problem Formulation
41(1)
4.2 Joint Diagonalization
42(1)
4.3 Linear Filtering
43(1)
4.4 Performance Measures
44(3)
4.4.1 Noise Reduction
44(1)
4.4.2 Desired Signal Distortion
45(1)
4.4.3 MSE Criterion
46(1)
4.5 Optimal Linear Filters
47(3)
4.5.1 Maximum SNR
47(1)
4.5.2 Minimum Distortion
47(1)
4.5.3 Wiener
48(1)
4.5.4 Tradeoff
49(1)
4.6 Experimental Results
50(25)
References
57(1)
4.A MATLAB Code
58(1)
4.A.1 Main Scripts
58(9)
4.A.2 Functions
67(8)
5 Multichannel Signal Enhancement in the Time Domain
75(40)
5.1 Signal Model and Problem Formulation
75(3)
5.2 Linear Filtering with a Rectangular Matrix
78(2)
5.3 Performance Measures
80(3)
5.3.1 Noise Reduction
80(1)
5.3.2 Desired Signal Distortion
81(1)
5.3.3 MSE Criterion
82(1)
5.4 Optimal Rectangular Linear Filtering Matrices
83(5)
5.4.1 Maximum SNR
83(1)
5.4.2 Wiener
84(1)
5.4.3 MVDR
85(1)
5.4.4 Tradeoff
86(2)
5.5 Experimental Results
88(10)
References
97(1)
5.5 MATLAB Code
98(17)
5.5.1 Main Scripts
98(10)
5.5.2 Functions
108(7)
6 Multichannel Signal Enhancement in the STFT Domain
115(34)
6.1 Signal Model and Problem Formulation
115(2)
6.2 Direct Approach for Signal Enhancement
117(6)
6.3 Indirect Approach for Signal Enhancement
123(2)
6.4 Experimental Results
125(7)
References
131(1)
6.4 MATLAB Code
132(17)
6.4.1 Main Scripts
132(9)
6.4.2 Functions
141(8)
7 Binaural Signal Enhancement in the Time Domain
149(16)
7.1 Signal Model and Problem Formulation
149(5)
7.2 Widely Linear Filtering with a Rectangular Matrix
154(1)
7.3 Performance Measures
155(3)
7.3.1 Noise Reduction
155(1)
7.3.2 Desired Signal Distortion
156(1)
7.3.3 MSE Criterion
157(1)
7.4 Optimal Rectangular Linear Filtering Matrices
158(7)
7.4.1 Maximum SNR
159(1)
7.4.2 Wiener
160(1)
7.4.3 MVDR
161(1)
7.4.4 Tradeoff
162(1)
References
163(2)
A Auxiliary MATLAB Functions 165(4)
References 169(2)
Index 171