Blind Equalization And System Identification
by Chi, Chong-yung; Feng, Chih-chun; Chen, Chii-horng; Chen, Ching-yungRent Textbook
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Summary
Author Biography
Table of Contents
| 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 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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