Neural Network Models

Theory and Projects

By: Philippe de Wilde

Write A Review

Paperback | 30 May 1997 | Edition Number 2

At a Glance

Paperback
188 Pages

Edition Type
Revised

Dimensions(cm)
24.13 x 16.51 x 1.91

Paperback

$84.99

or 4 interest-free payments of $21.25 with

Ships in 7 to 10 business days

Providing an in-depth treatment of neural network models, this volume explains and proves the main results in a clear and accessible way. It presents the essential principles of nonlinear dynamics as derived from neurobiology, and investigates the stability, convergence behaviour and capacity of networks. Also included are sections on stochastic networks and simulated annealing, presented using Markov processes rather than statistical physics, and a chapter on backpropagation. Each chapter ends with a suggested project designed to help the reader develop an integrated knowledge of the theory, placing it within a practical application domain. Neural Network Models: Theory and Projects concentrates on the essential parameters and results that will enable the reader to design hardware or software implementations of neural networks and to assess critically existing commercial products.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Science Physics Electricity Computer Networking & Communications Engineering & Technology Energy Technology & Engineering Electrical Engineering

Table of contents: Preface
Key concepts in neural networks
Backpropagation
Neurons in the Brain
The Fundamental System of Differential Equations
Synchronous and Discrete Networks
Linear Capacity
Capacity from a Signal to Noise Ratio
Neural Networks and Markov Chains
Bibliography
Index
Table of Contents provided by Publisher. All Rights Reserved.

Neural Network Models

Theory and Projects

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Neural Networks & Fuzzy Systems

Principles of Computational Neuroscience

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e

Concepts, Tools, and Techniques to Build Intelligent Systems

Practical Machine Learning for Computer Vision

End-to-End Machine Learning for Images

Effective Machine Learning Teams

Best Practices for ML Practitioners

Intelligent Estimation

A Soft Computing Paradigm

Applications of Quantum Field Theory to Problems in Machine Learning

Advanced Techniques Based on Path Integrals

Pyramidal Neural Networks

Psychology Revivals

Generative AI in Higher Education: Ethical Governance, Skills, and Employability

Volume 2

Mathematical Foundations of Deep Learning

Theory and Algorithms

Artificial Intelligence in Tribology

Decision-Making and Analytics

Data-Driven Business Intelligence and Optimization

Quantum Learning

Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education

Perceptive Machines

The Future of Feeling AI and What It Means for Humanity

Perceptive Machines

The Future of Feeling AI and What It Means for Humanity

Fuzzy Model-Based Sliding Mode Control of Complex Nonlinear Systems

Engineering Mathematics and Operations Research

Intelligent Mobile and IoT Ecosystems

Bridging Cloud, Fog, Edge, and AI

Quantum Artificial Intelligence

Technologies, Algorithms and Programming

Uncertain Data Analysis

Fuzzy Vector Algorithms

Uncertain Data Analysis

Fuzzy Vector Algorithms

Technological Innovation and Sustainability through AI

Cutting-Edge Solutions for a Sustainable Future

Reinforcement Learning Explained

A Practical Problem-Solving Approach

Network Models in Finance

Expanding the Tools for Portfolio and Risk Management

Autonomous Cyber Resilience

Machine Learning Interviews

Kickstart Your Machine Learning Career

This product is categorised by