Complex-Valued Neural Networks: Utilizing High-Dimensional Parameters: Utilizing High-Dimensional ParametersRecent 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. |
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Contents
27 | |
Kolmogorovs Spline ComplexNetwork and Adaptive DynamicModeling of Data | 56 |
Dynamics and Applications | 79 |
Global Stability Analysis forComplexValued RecurrentNeural Networks and ItsApplication to ConvexOptimization Problems | 104 |
Models of ComplexValuedHopfieldType Neural Networksand Their Dynamics | 123 |
ComplexValued SymmetricRadial Basis Function Networkfor Beamforming | 143 |
ComplexValued NeuralNetworks for Equalization ofCommunication Channels | 168 |
Learning Algorithms forComplexValued NeuralNetworks in CommunicationSignal Processing and AdaptiveEqualization as its Application | 194 |
Flexible Blind Signal Separationin the Complex Domain | 284 |
Its Performance and Applications | 325 |
Neuromorphic AdiabaticQuantum Computation | 352 |
Attractors and Energy Spectrumof Neural Structures Based onthe Model of the QuantumHarmonic Oscillator | 376 |
Fundamental Properties andApplications | 411 |
440 | |
About the Contributors | 470 |
476 | |
Design by Using GeneralizedProjection Rule | 236 |
A Method of Estimation forMagnetic ResonanceSpectroscopy UsingComplexValued NeuralNetworks | 256 |
Other editions - View all
Complex-valued Neural Networks: Utilizing High-dimensional Parameters Tohru Nitta No preview available - 2009 |