Complex-Valued Neural Networks
About this book
Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applicationsComplex-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 networks Quaternionic neural networks Clifford-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.
Reader Profile
· 196 pages · ≈ 3 h 38 m · Moderate
How long does it take to read Complex-Valued Neural Networks?
About ≈ 3 h 38 m — 196 pages, assuming roughly 250 words per page at 225 words per minute.
How many pages is Complex-Valued Neural Networks?
196 pages in its most-read edition.
Is Complex-Valued Neural Networks in the public domain?
No — it is still under copyright.
Who wrote Complex-Valued Neural Networks?
Akira Hirose.