Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition

by Sandhya Samarasinghe

Overview

In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks.

Beginning with an introductory discussion on the role of neural networks in

Product Details

ISBN-13:	9781040163368
Publisher:	CRC Press
Publication date:	04/19/2016
Sold by:	Barnes & Noble
Format:	eBook
Pages:	570
File size:	11 MB
Note:	This product may take a few minutes to download.

Table of Contents

Complexity and Challenges in Understanding Biological, Ecological, and Natural Systems. Evolution of Neural Learning Concepts. Overview of Neural Network Architectures for Practical Data Analysis. Multi-Layer Perceptron Network and Self Organizing Maps and Practical Examples.. In-Depth Look at Data Prior to Modeling. Issues of Model Validation Involving Complex Data. Uncertainty and sensitivity assessment of Models. Time-Series Analysis with Recurrent Networks and Practical Application Case Studies. Comparison with Relevant Statistical Methods. New Directions and Future Potential of Neural Networks.

Editorial Reviews

"Beginning with the basics, she [Samarasinghe] explains a variety of neural networks' internal workings, and how to apply them to solve real problems."

-SciTech Book News, December 2006

From the Publisher