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Complex-Valued Neural Networks with Multi-Valued Neurons Volume 353 by Aizenberg, Igor is a nonfiction available to read on EtoBox.

What is Complex-Valued Neural Networks with Multi-Valued Neurons Volume 353 about?

Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book is devoted to the Multi-Valued Neuron (MVN) and MVN-based neural networks. It contains a comprehensive observation of MVN theory, its learning, and applications. MVN is a complex-valued neuron whose inputs and output are located on the unit circle. Its activation function is a function only of argument (phase) of the weighted sum. MVN derivative-free learning is based on the error-correction rule. A single MVN can learn those input/output mappings that are non-linearly separable in the real domain. Such classical non-linearly separable problems as XOR and Parity n are the simplest that can be learned by a single MVN. Another important advantage of MVN is a proper treatment of the phase information. These properties of MVN become even more remarkable when this neuron is used as a basic one in neural networks. The Multilayer Neural Network based on Multi-Valued Neurons (MLMVN) is an MVN-based feedforward neural network. Its backpropagation learning algorithm is derivative-free and based on the error-correction rule. It does not suffer from the lo

Who reads Complex-Valued Neural Networks with Multi-Valued Neurons Volume 353?

Author

Aizenberg, Igor

Publisher

Springer Berlin Heidelberg : Imprint: Springer

Published

2011

Language

EN

ISBN

9783642203527

Category

nonfiction

Subjects

Computer Science, Engineering, Science