Complex-valued Neural Networks: Utilizing High-dimensional Parameters (Premier Reference Source)

Recent research indicates that complex-valued neural networks whose parameters (weights and threshold values) are all complex numbers are in fact useful, containing characteristics bringing about many significant applications. Complex-Valued Neural Networks: Utilizing High-Dimensional Parameters covers the current state-of-the-art theories and applications of neural networks with high-dimensional parameters such as complex-valued neural networks, quantum neural networks, quaternary neural networks, and Clifford neural networks, which have been developing in recent years. Graduate students and researchers will easily acquire the fundamental knowledge needed to be at the forefront of research, while practitioners will readily absorb the materials required for the applications. Title ......Page 2 Table of Contents......Page 6 Detailed Table of Contents......Page 9 Foreword......Page 14 Preface......Page 16 Acknowledgment......Page 24 Complex-Valued Boltzmann Manifold......Page 26 Complex-Valued Neural Network and Inverse Problems......Page 52 Kolmogorov’s Spline Complex Network and Adaptive Dynamic Modeling of Data......Page 81 A Complex-Valued Hopfield Neural Network: Dynamics and Applications......Page 104 Global Stability Analysis for Complex-Valued Recurrent Neural Networks and Its Application to Convex Optimization Problems......Page 129 Models of Complex-Valued Hopfield-Type Neural Networks and Their Dynamics......Page 148 Complex-Valued Symmetric Radial Basis Function Network for Beamforming......Page 168 Complex-Valued Neural Networks for Equalization of Communication Channels......Page 193 Learning Algorithms for Complex-Valued Neural Networks in Communication Signal Processing and Adaptive Equalization as its Application......Page 219 Image Reconstruction by the Complex-Valued Neural Networks: Design by Using Generalized Projection Rule......Page 261 A Method of Estimation for Magnetic Resonance Spectroscopy Using Complex-Valued Neural Networks......Page 281 Flexible Blind Signal Separation in the Complex Domain......Page 309 Qubit Neural Network:Its Performance and Applications......Page 350 Neuromorphic Adiabatic Quantum Computation......Page 377 Attractors and Energy Spectrum of Neural Structures Based on the Model of the Quantum Harmonic Oscillator......Page 401 Quaternionic Neural Networks: Fundamental Properties and Applications......Page 436 Compilation of References......Page 465 About the Contributors......Page 495 Index......Page 501 This Book Covers The Current State-of-the-art Theories And Applications Of Neural Networks With High-dimensional Parameters--provided By Publisher. Tohru Nitta, [editor]. Premier Reference Source--cover. Includes Bibliographical References (pages 440-469) And Index.