Efficient gradient computation for continuous and discrete time-dependent neural networks
Author: Stefan Miesbach
Publisher:
Published: 1991
Total Pages: 12
ISBN-13:
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Zeroing Dynamics, Gradient Dynamics, and Newton Iterations
Author: Yunong Zhang
Publisher: CRC Press
Published: 2018-10-09
Total Pages: 310
ISBN-13: 1498753787
DOWNLOAD EBOOKNeural networks and neural dynamics are powerful approaches for the online solution of mathematical problems arising in many areas of science, engineering, and business. Compared with conventional gradient neural networks that only deal with static problems of constant coefficient matrices and vectors, the authors’ new method called zeroing dynamics solves time-varying problems. Zeroing Dynamics, Gradient Dynamics, and Newton Iterations is the first book that shows how to accurately and efficiently solve time-varying problems in real-time or online using continuous- or discrete-time zeroing dynamics. The book brings together research in the developing fields of neural networks, neural dynamics, computer mathematics, numerical algorithms, time-varying computation and optimization, simulation and modeling, analog and digital hardware, and fractals. The authors provide a comprehensive treatment of the theory of both static and dynamic neural networks. Readers will discover how novel theoretical results have been successfully applied to many practical problems. The authors develop, analyze, model, simulate, and compare zeroing dynamics models for the online solution of numerous time-varying problems, such as root finding, nonlinear equation solving, matrix inversion, matrix square root finding, quadratic optimization, and inequality solving.
Neural Networks
Author: Berndt Müller
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 340
ISBN-13: 3642577601
DOWNLOAD EBOOKNeural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.
1991 IEEE International Joint Conference on Neural Networks
Author:
Publisher:
Published: 1991
Total Pages: 974
ISBN-13:
DOWNLOAD EBOOK1991 IEEE International Joint Conference on Neural Networks
Author: Institute of Electrical and Electronics Engineers
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Published: 1991
Total Pages: 992
ISBN-13:
DOWNLOAD EBOOKMajor conference in the field of neural networks with the latest theoretical and practical developments. Topics include: applications, image and signal processing, data analysis, mathematical foundations, neural network architectures, and robotics and control.
1993 IEEE International Conference on Neural Networks, San Francisco, California, March 28-April 1, 1993
Author:
Publisher:
Published: 1993
Total Pages: 592
ISBN-13:
DOWNLOAD EBOOKNeural Dynamics for Time-varying Problems
Author: Long Jin
Publisher: Springer Nature
Published:
Total Pages: 213
ISBN-13: 3031685946
DOWNLOAD EBOOKThe Engineering Index Annual
Author:
Publisher:
Published: 1992
Total Pages: 2264
ISBN-13:
DOWNLOAD EBOOKSince its creation in 1884, Engineering Index has covered virtually every major engineering innovation from around the world. It serves as the historical record of virtually every major engineering innovation of the 20th century. Recent content is a vital resource for current awareness, new production information, technological forecasting and competitive intelligence. The world?s most comprehensive interdisciplinary engineering database, Engineering Index contains over 10.7 million records. Each year, over 500,000 new abstracts are added from over 5,000 scholarly journals, trade magazines, and conference proceedings. Coverage spans over 175 engineering disciplines from over 80 countries. Updated weekly.
Zhang Time Discretization (ZTD) Formulas and Applications
Author: Yunong Zhang
Publisher: CRC Press
Published: 2024-08-07
Total Pages: 356
ISBN-13: 104009161X
DOWNLOAD EBOOKThis book aims to solve the discrete implementation problems of continuous-time neural network models while improving the performance of neural networks by using various Zhang Time Discretization (ZTD) formulas. The authors summarize and present the systematic derivations and complete research of ZTD formulas from special 3S-ZTD formulas to general NS-ZTD formulas. These finally lead to their proposed discrete-time Zhang neural network (DTZNN) algorithms, which are more efficient, accurate, and elegant. This book will open the door to scientific and engineering applications of ZTD formulas and neural networks, and will be a major inspiration for studies in neural network modeling, numerical algorithm design, prediction, and robot manipulator control. The book will benefit engineers, senior undergraduates, graduate students, and researchers in the fields of neural networks, computer mathematics, computer science, artificial intelligence, numerical algorithms, optimization, robotics, and simulation modeling.
