Neural Network Data Analysis Using Simulnet™

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Neural Network Data Analysis Using Simulnet™ by Edward J. Rzempoluck, Springer New York
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Edward J. Rzempoluck ISBN: 9781461217466
Publisher: Springer New York Publication: December 6, 2012
Imprint: Springer Language: English
Author: Edward J. Rzempoluck
ISBN: 9781461217466
Publisher: Springer New York
Publication: December 6, 2012
Imprint: Springer
Language: English

This book and software package complements the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural network functions such as multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalised regression neural networks, learning quantizer networks, and self-organising feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: genetic algorithms, probabilistic networks, as well as a number of related techniques that support these. Readers are assumed to have a basic understanding of computers and elementary mathematics, allowing them to quickly conduct sophisticated hands-on analyses of data sets.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book and software package complements the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural network functions such as multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalised regression neural networks, learning quantizer networks, and self-organising feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: genetic algorithms, probabilistic networks, as well as a number of related techniques that support these. Readers are assumed to have a basic understanding of computers and elementary mathematics, allowing them to quickly conduct sophisticated hands-on analyses of data sets.

More books from Springer New York

Cover of the book Nanofins by Edward J. Rzempoluck
Cover of the book Reviews of Environmental Contamination and Toxicology by Edward J. Rzempoluck
Cover of the book Time-Domain Ultra-Wideband Radar, Sensor and Components by Edward J. Rzempoluck
Cover of the book Multisensory Object Perception in the Primate Brain by Edward J. Rzempoluck
Cover of the book Location, Localization, and Localizability by Edward J. Rzempoluck
Cover of the book Pathologic Myopia by Edward J. Rzempoluck
Cover of the book Neuromuscular Disorders in Clinical Practice by Edward J. Rzempoluck
Cover of the book The Design and Analysis of Computer Experiments by Edward J. Rzempoluck
Cover of the book Loudness by Edward J. Rzempoluck
Cover of the book Reviews of Environmental Contamination and Toxicology by Edward J. Rzempoluck
Cover of the book Pediatric Cranial MRI by Edward J. Rzempoluck
Cover of the book Industrial Color Physics by Edward J. Rzempoluck
Cover of the book Handbook of Parathyroid Diseases by Edward J. Rzempoluck
Cover of the book Dynamic Models of Infectious Diseases by Edward J. Rzempoluck
Cover of the book Working with Assumptions in International Development Program Evaluation by Edward J. Rzempoluck
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy