1.

Record Nr.

UNINA9910957230303321

Autore

Kattan Ali

Titolo

Artificial neural network training and software implementation techniques / / Ali Kattan, Rosni Abdullah and Zong Woo Geem

Pubbl/distr/stampa

Hauppauge, N.Y., : Nova Science Publishers, c2011

ISBN

1-62257-103-7

Edizione

[1st ed.]

Descrizione fisica

1 online resource (68 p.)

Collana

Computer networks

Novinka

Altri autori (Persone)

AbdullahRosni

GeemZong Woo

Disciplina

006.3/2

Soggetti

Neural networks (Computer science)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p.[43]-53) and index.

Nota di contenuto

Feed-forward neural networks -- FFANN software simulation -- FFANN training concept -- Trajectory-driven training paradigm -- Evolutionary-based training paradigm -- FFANN simulation utilizing graphic-processing units.

Sommario/riassunto

Artificial neural networks (ANN) are widely used in diverse fields of science and industry. Though there have been numerous techniques used for their implementations, the choice of a specific implementation is subjected to different factors including cost, accuracy, processing speed and overall performance. Featured with synaptic plasticity, the process of training is concerned with adjusting the individual weights between each of the individual ANN neurons until we can achieve close to the desired output. This book introduces the common trajectory-driven and evolutionary-based ANN training algorithms.