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Book details
File Size: 4.66 MB
Format: pdf
Print Length: 119 pages
Simultaneous Device Usage: Unlimited
Publisher: Heaton Research, Inc. (April 3, 2012)
Publication Date: April 3, 2012
Sold by: Amazon.com Services LLC
Language: English
ASIN: B00845UQL6
This book introduces the reader to the basic math used for neural network calculation. This book assumes the reader has only knowledge of college algebra and computer programming. This book begins by showing how to calculate output of a neural network and moves on to more advanced training methods such as backpropagation, resilient propagation and Levenberg Marquardt optimization. The mathematics needed by these techniques is also introduced. Mathematical topics covered by this book include first, second, Hessian matrices, gradient descent and partial derivatives. All mathematical notation introduced is explained. Neural networks covered include the feedforward neural network and the self-organizing map. This book provides an ideal supplement to our other neural books. This book is ideal for the reader, without a formal mathematical background, that seeks a more mathematical description of neural networks.
