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Statistical Mechanics of Neural Networks

2022-01-04 Science
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Release : 2022-01-04
Genre : Science
Kind : eBook
Book Rating : 708/5 ( reviews)

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Book Synopsis Statistical Mechanics of Neural Networks by : Haiping Huang

Download or read book Statistical Mechanics of Neural Networks written by Haiping Huang. This book was released on 2022-01-04. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks. The book discusses in details important concepts and techniques including the cavity method, the mean-field theory, replica techniques, the Nishimori condition, variational methods, the dynamical mean-field theory, unsupervised learning, associative memory models, perceptron models, the chaos theory of recurrent neural networks, and eigen-spectrums of neural networks, walking new learners through the theories and must-have skillsets to understand and use neural networks. The book focuses on quantitative frameworks of neural network models where the underlying mechanisms can be precisely isolated by physics of mathematical beauty and theoretical predictions. It is a good reference for students, researchers, and practitioners in the area of neural networks.

Statistical Field Theory for Neural Networks

2020-08-20 Science
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Release : 2020-08-20
Genre : Science
Kind : eBook
Book Rating : 44X/5 ( reviews)

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Book Synopsis Statistical Field Theory for Neural Networks by : Moritz Helias

Download or read book Statistical Field Theory for Neural Networks written by Moritz Helias. This book was released on 2020-08-20. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks. These powerful analytical techniques, which are well established in other fields of physics, are the basis of current developments and offer solutions to pressing open problems in theoretical neuroscience and also machine learning. They enable a systematic and quantitative understanding of the dynamics in recurrent and stochastic neuronal networks. This book is intended for physicists, mathematicians, and computer scientists and it is designed for self-study by researchers who want to enter the field or as the main text for a one semester course at advanced undergraduate or graduate level. The theoretical concepts presented in this book are systematically developed from the very beginning, which only requires basic knowledge of analysis and linear algebra.

Statistical Mechanics of Learning

2001-03-29 Computers
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Release : 2001-03-29
Genre : Computers
Kind : eBook
Book Rating : 796/5 ( reviews)

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Book Synopsis Statistical Mechanics of Learning by : A. Engel

Download or read book Statistical Mechanics of Learning written by A. Engel. This book was released on 2001-03-29. Available in PDF, EPUB and Kindle. Book excerpt: Learning is one of the things that humans do naturally, and it has always been a challenge for us to understand the process. Nowadays this challenge has another dimension as we try to build machines that are able to learn and to undertake tasks such as datamining, image processing and pattern recognition. We can formulate a simple framework, artificial neural networks, in which learning from examples may be described and understood. The contribution to this subject made over the last decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics and include many examples and exercises to make a book that can be used with courses, or for self-teaching, or as a handy reference.

Neural Network Modeling

2018-02-06 Technology & Engineering
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Release : 2018-02-06
Genre : Technology & Engineering
Kind : eBook
Book Rating : 969/5 ( reviews)

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Book Synopsis Neural Network Modeling by : P. S. Neelakanta

Download or read book Neural Network Modeling written by P. S. Neelakanta. This book was released on 2018-02-06. Available in PDF, EPUB and Kindle. Book excerpt: Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.

Models of Neural Networks III

2012-12-06 Science
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Release : 2012-12-06
Genre : Science
Kind : eBook
Book Rating : 231/5 ( reviews)

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Book Synopsis Models of Neural Networks III by : Eytan Domany

Download or read book Models of Neural Networks III written by Eytan Domany. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu ment since has been shown to be rather susceptible to generalization.

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