Presents the latest advances in complex-valued neural networks
by demonstrating the theory in a wide range of applications
Complex-valued neural networks is a rapidly developing neural
network framework that utilizes complex arithmetic, exhibiting
specific characteristics in its learning, self-organizing, and
processing dynamics. They are highly suitable for processing
complex amplitude, composed of amplitude and phase, which is one of
the core concepts in physical systems to deal with electromagnetic,
light, sonic/ultrasonic waves as well as quantum waves, namely,
electron and superconducting waves. This fact is a critical
advantage in practical applications in diverse fields of
engineering, where signals are routinely analyzed and processed in
time/space, frequency, and phase domains.
"Complex-Valued Neural Networks: Advances and Applications"
covers cutting-edge topics and applications surrounding this timely
subject. Demonstrating advanced theories with a wide range of
applications, including communication systems, image processing
systems, and brain-computer interfaces, this text offers
comprehensive coverage of: Conventional complex-valued neural
networksQuaternionic neural networksClifford-algebraic neural
networks
Presented by international experts in the field, "Complex-Valued
Neural Networks: Advances and Applications" is ideal for
advanced-level computational intelligence theorists,
electromagnetic theorists, and mathematicians interested in
computational intelligence, artificial intelligence, machine
learning theories, and algorithms.
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