Main description:

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.

Contents:

Attractors and energy spectrum of neural structures; Communication signal processing; Complex-valued magnetic resonance images; Complex-valued neural network; Complex-valued recurrent neural networks; Complex-valued symmetric radial basis function network; Complex-valued time delay neural networks; Flexible blind signal separation; Global stability analysis; Image reconstruction; Magnetic resonance spectroscopy; Model of the quantum harmonic oscillator; Quantum neural networks; Quaternionic neural networks; Qubit neural networks.