SIMON HAYKIN, PhD, is University Professor and Director of the Adaptive Systems Laboratory at McMaster University.

• Contributors viiPreface xi1 Introduction 1Simon Haykin1.1 Why Adaptive Filtering?  11.2 Supervised and Unsupervised Forms of Adaptive Filtering 21.3 Two Important Unsupervised Signal-Processing Tasks 31.4 Three Fundamental Approaches to Unsupervised Adaptive Filtering 61.5 Organization of Volume II 10References 112 The Core of FSE-CMA Behavior Theory 13C. R. Johnson, Jr., P. Schniter, I. Fijalkow, L. Tong, J. D. Behm, M. G. Larimore, D. R. Brown, R. A. Casas, T. J. Endres, S. Lambotharan, A. Touzni, H. H. Zeng, M. Green, and J. R. Treichler2.1 Introduction 142.2 MMSE Equalization and LMS 222.3 The CM Criterion and CMA 412.4 CMA-Adapted-Equalizer Design Issues with Illustrative Examples 752.5 Case Studies 892.6 Conclusions 106References 1083 Relationships between Blind Deconvolution and Blind Source Separation 113Scott C. Douglas and Simon Haykin3.1 Introduction 1133.2 Problem Descriptions 1173.3 Algorithmic Relationships 1223.4 Structural Relationships 1293.5 Extensions 1403.6 Conclusions 142References 1424 Blind Separation of Independent Sources Based on Multiuser Kurtosis Optimization Criteria 147Constantinos B. Papadias4.1 Introduction 1484.2 Problem Formulation and Assumptions 1504.3 Review: The Single-User Equalization Problem 1544.4 Necessary and Su½cient Conditions for BSS 1604.5 Unconstrained Criteria: The MU-CM Approach 1624.6 Constrained Criteria: The MUK Approach 1654.7 Numerical Examples 1714.8 Conclusions 175References 176Index 181

SIMON HAYKIN, PhD, is University Professor and Director of the Adaptive Systems Laboratory at McMaster University.

• Contributors viiPreface xi1 Introduction 1Simon Haykin1.1 Why Adaptive Filtering?  11.2 Supervised and Unsupervised Forms of Adaptive Filtering 21.3 Two Important Unsupervised Signal-Processing Tasks 31.4 Three Fundamental Approaches to Unsupervised Adaptive Filtering 61.5 Organization of Volume II 10References 112 The Core of FSE-CMA Behavior Theory 13C. R. Johnson, Jr., P. Schniter, I. Fijalkow, L. Tong, J. D. Behm, M. G. Larimore, D. R. Brown, R. A. Casas, T. J. Endres, S. Lambotharan, A. Touzni, H. H. Zeng, M. Green, and J. R. Treichler2.1 Introduction 142.2 MMSE Equalization and LMS 222.3 The CM Criterion and CMA 412.4 CMA-Adapted-Equalizer Design Issues with Illustrative Examples 752.5 Case Studies 892.6 Conclusions 106References 1083 Relationships between Blind Deconvolution and Blind Source Separation 113Scott C. Douglas and Simon Haykin3.1 Introduction 1133.2 Problem Descriptions 1173.3 Algorithmic Relationships 1223.4 Structural Relationships 1293.5 Extensions 1403.6 Conclusions 142References 1424 Blind Separation of Independent Sources Based on Multiuser Kurtosis Optimization Criteria 147Constantinos B. Papadias4.1 Introduction 1484.2 Problem Formulation and Assumptions 1504.3 Review: The Single-User Equalization Problem 1544.4 Necessary and Su½cient Conditions for BSS 1604.5 Unconstrained Criteria: The MU-CM Approach 1624.6 Constrained Criteria: The MUK Approach 1654.7 Numerical Examples 1714.8 Conclusions 175References 176Index 181

SIMON HAYKIN, PhD, is University Professor and Director of the Adaptive Systems Laboratory at McMaster University.

• Contributors viiPreface xi1 Introduction 1Simon Haykin1.1 Why Adaptive Filtering?  11.2 Supervised and Unsupervised Forms of Adaptive Filtering 21.3 Two Important Unsupervised Signal-Processing Tasks 31.4 Three Fundamental Approaches to Unsupervised Adaptive Filtering 61.5 Organization of Volume II 10References 112 The Core of FSE-CMA Behavior Theory 13C. R. Johnson, Jr., P. Schniter, I. Fijalkow, L. Tong, J. D. Behm, M. G. Larimore, D. R. Brown, R. A. Casas, T. J. Endres, S. Lambotharan, A. Touzni, H. H. Zeng, M. Green, and J. R. Treichler2.1 Introduction 142.2 MMSE Equalization and LMS 222.3 The CM Criterion and CMA 412.4 CMA-Adapted-Equalizer Design Issues with Illustrative Examples 752.5 Case Studies 892.6 Conclusions 106References 1083 Relationships between Blind Deconvolution and Blind Source Separation 113Scott C. Douglas and Simon Haykin3.1 Introduction 1133.2 Problem Descriptions 1173.3 Algorithmic Relationships 1223.4 Structural Relationships 1293.5 Extensions 1403.6 Conclusions 142References 1424 Blind Separation of Independent Sources Based on Multiuser Kurtosis Optimization Criteria 147Constantinos B. Papadias4.1 Introduction 1484.2 Problem Formulation and Assumptions 1504.3 Review: The Single-User Equalization Problem 1544.4 Necessary and Su½cient Conditions for BSS 1604.5 Unconstrained Criteria: The MU-CM Approach 1624.6 Constrained Criteria: The MUK Approach 1654.7 Numerical Examples 1714.8 Conclusions 175References 176Index 181