Introduction | p. 1 |
References | p. 8 |
Mathematical Background | p. 13 |
Linear Algebra | p. 13 |
Vectors and Vector Spaces | p. 13 |
Matrices | p. 17 |
Matrix Decomposition | p. 23 |
Mathematical Analysis | p. 26 |
Sequences | p. 27 |
Series | p. 30 |
Hilbert Spaces, Sequence Spaces and Function Spaces | p. 33 |
Fourier Series | p. 38 |
Optimization Theory | p. 41 |
Vector Derivatives | p. 42 |
Necessary and Sufficient Conditions for Solutions | p. 45 |
Gradient-Type Optimization Methods | p. 48 |
Least-Squares Method | p. 62 |
Full-Rank Overdetermined Least-Squares Problem | p. 64 |
Generic Least-Squares Problem | p. 65 |
Summary | p. 67 |
Proof of Theorem 2.15 | p. 68 |
Some Terminologies of Functions | p. 72 |
Proof of Theorem 2.33 | p. 74 |
Proof of Theorem 2.36 | p. 75 |
Proof of Theorem 2.38 | p. 76 |
Proof of Theorem 2.46 | p. 77 |
Problems | p. 79 |
Computer Assignments | p. 81 |
References | p. 81 |
Fundamentals of Statistical Signal Processing | p. 83 |
Discrete-Time Signals and Systems | p. 83 |
Time-Domain Characterization | p. 83 |
Transformation Tools | p. 86 |
Transform-Domain Characterization | p. 91 |
Random Variables | p. 96 |
Statistical Characterization | p. 96 |
Moments | p. 99 |
Cumulants | p. 104 |
Some Useful Distributions | p. 109 |
Random Processes | p. 119 |
Statistical Characterization | p. 119 |
Stationary Processes | p. 123 |
Cyclostationary Processes | p. 139 |
Estimation Theory | p. 147 |
Estimation Problem | p. 147 |
Properties of Estimators | p. 150 |
Maximum-Likelihood Estimation | p. 158 |
Method of Moments | p. 160 |
Minimum Mean-Square-Error Estimation | p. 164 |
Wiener Filtering | p. 166 |
Least-Squares Estimation | p. 169 |
Summary | p. 172 |
Relationship between Cumulants and Moments | p. 172 |
Proof of Theorem 3.47 | p. 173 |
Proof of Theorem 3.52 | p. 174 |
Problems | p. 175 |
Computer Assignments | p. 178 |
References | p. 180 |
SISO Blind Equalization Algorithms | p. 183 |
Linear Equalization | p. 183 |
Blind Equalization Problem | p. 183 |
Peak Distortion and MMSE Equalization Criteria | p. 187 |
SOS Based Blind Equalization Approach: Linear Prediction | p. 190 |
Forward and Backward Linear Prediction | p. 191 |
Levinson-Durbin Recursion | p. 196 |
Lattice Linear Prediction Error Filters | p. 202 |
Linear Predictive Deconvolution | p. 205 |
HOS Based Blind Equalization Approaches | p. 209 |
Maximum Normalized Cumulant Equalization Algorithm | p. 211 |
Super-Exponential Equalization Algorithm | p. 214 |
Algorithm Analyses | p. 221 |
Algorithm Improvements | p. 226 |
Simulation Examples for Algorithm Tests | p. 231 |
Some Applications | p. 235 |
Seismic Exploration | p. 236 |
Speech Signal Processing | p. 245 |
Baud-Spaced Equalization in Digital Communications | p. 252 |
Summary and Discussion | p. 265 |
Proof of Property 4.17 | p. 267 |
Problems | p. 268 |
Computer Assignments | p. 269 |
References | p. 270 |
MIMO Blind Equalization Algorithms | p. 275 |
MIMO Linear Time-Invariant Systems | p. 275 |
Definitions and Properties | p. 275 |
Smith-McMillan Form | p. 281 |
Linear Equalization | p. 286 |
Blind Equalization Problem | p. 287 |
Peak Distortion and MMSE Equalization Criteria | p. 290 |
SOS Based Blind Equalization Approaches | p. 292 |
Blind SIMO Equalization | p. 292 |
Blind MIMO Equalization | p. 300 |
HOS Based Blind Equalization Approaches | p. 304 |
Temporally IID Inputs | p. 305 |
Temporally Colored Inputs | p. 314 |
Algorithm Tests | p. 318 |
Summary and Discussion | p. 325 |
Proof of Property 5.34 | p. 326 |
Proof of Property 5.35 | p. 328 |
A GCD Computation Algorithm | p. 329 |
Problems | p. 330 |
Computer Assignments | p. 330 |
References | p. 331 |
Applications of MIMO Blind Equalization Algorithms | p. 335 |
Fractionally Spaced Equalization in Digital Communications | p. 335 |
Blind Maximum Ratio Combining | p. 340 |
SIMO Blind System Identification | p. 342 |
MIMO-MNC Equalizer-System Relation | p. 344 |
Analysis on System Identification Based on MIMO-MNC Equalizer-System Relation | p. 345 |
SIMO Blind System Identification Algorithm | p. 346 |
Multiple Time Delay Estimation | p. 351 |
Model Assumptions | p. 351 |
MTDE with Space Diversity Gain | p. 352 |
Blind Beamforming for Source Separation | p. 357 |
Model Assumptions | p. 357 |
Blind Beamforming | p. 358 |
Multistage Source Separation | p. 359 |
Multiuser Detection in Wireless Communications | p. 362 |
Model Assumptions and Problem Statement | p. 363 |
Signature Waveform Matched Filtering Based Multiuser Detection | p. 364 |
Chip Waveform Matched Filtering Based Multiuser Detection | p. 369 |
Multiple Antennas Based Multiuser Detection | p. 375 |
Summary and Discussion | p. 378 |
Proof of Theorem 6.3 | p. 379 |
Proof of Fact 6.4 | p. 380 |
Proof of Property 6.10 | p. 381 |
Multichannel Levinson Recursion Algorithm | p. 383 |
Integrated Bispectrum Based Time Delay Estimation | p. 385 |
Problems | p. 387 |
Computer Assignments | p. 387 |
References | p. 388 |
Two-Dimensional Blind Deconvolution Algorithms | p. 391 |
Two-Dimensional Discrete-Space Signals, Systems and Random Processes | p. 391 |
2-D Deterministic Signals | p. 391 |
2-D Transforms | p. 393 |
2-D Linear Shift-Invariant Systems | p. 395 |
2-D Stationary Random Processes | p. 400 |
2-D Deconvolution | p. 402 |
Blind Deconvolution Problem | p. 402 |
Peak Distortion and Minimum Mean-Square-Error Deconvolution Criteria | p. 404 |
SOS Based Blind Deconvolution Approach: Linear Prediction | p. 406 |
HOS Based Blind Deconvolution Approaches | p. 409 |
2-D Maximum Normalized Cumulant Deconvolution Algorithm | p. 409 |
2-D Super-Exponential Deconvolution Algorithm | p. 413 |
Improvements on 2-D MNC Deconvolution Algorithm | p. 416 |
Simulation | p. 418 |
Summary and Discussion | p. 423 |
Problems | p. 424 |
Computer Assignments | p. 424 |
References | p. 425 |
Applications of Two-Dimensional Blind Deconvolution Algorithms | p. 427 |
Nonparametric Blind System Identification and Texture Synthesis | p. 427 |
Nonparametric 2-D BSI | p. 428 |
Texture Synthesis | p. 434 |
Parametric Blind System Identification and Texture Image Classification | p. 438 |
Parametric 2-D BSI | p. 439 |
Texture Image Classification | p. 449 |
Summary and Discussion | p. 454 |
Proof of Property 8.2 | p. 455 |
Proof of Property 8.3 | p. 456 |
Proof of Theorem 8.6 | p. 458 |
Proof of Fact 8.9 | p. 459 |
Problems | p. 460 |
Computer Assignments | p. 460 |
References | p. 461 |
Index | p. 463 |
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