Deep Neural Networks - WASD Neuronet Models, Algorithms, and Applications (Paperback)

Toward Deep Neural Networks: WASD Neuronet Models, Algorithms, and Applications introduces the outlook and extension toward deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors’ 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet, and allows reader to extend the techniques in the book to solve scientific and engineering problems. The book will be of interest to engineers, senior undergraduates, postgraduates, and researchers in the fields of neuronets, computer mathematics, computer science, artificial intelligence, numerical algorithms, optimization, simulation and modeling, deep learning, and data mining. Features Focuses on neuronet models, algorithms, and applications Designs, constructs, develops, analyzes, simulates and compares various WASD neuronet models, such as single-input WASD neuronet models, two-input WASD neuronet models, three-input WASD neuronet models, and general multi-input WASD neuronet models for function data approximations Includes real-world applications, such as population prediction Provides complete mathematical foundations, such as Weierstrass approximation, Bernstein polynomial approximation, Taylor polynomial approximation, and multivariate function approximation, exploring the close integration of mathematics (i.e., function approximation theories) and computers (e.g., computer algorithms) Utilizes the authors' 20 years of research on neuronets

General

Imprint:	Crc Press
Country of origin:	United Kingdom
Series:	Chapman & Hall/CRC Artificial Intelligence and Robotics Series
Release date:	September 2020
First published:	2019
Authors:	Yunong Zhang • Dechao Chen • Chengxu Ye
Dimensions:	254 x 178mm (L x W)
Format:	Paperback
Pages:	340
ISBN-13:	978-0-367-65649-2
Categories:	Books
LSN:	0-367-65649-3
Barcode:	9780367656492

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