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

• Autore: Kattan Ali
• Pubblicazione: Hauppauge, N.Y., : Nova Science Publishers, c2011
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (68 p.)
• Disciplina: 006.3/2
• Soggetto topico: Neural networks (Computer science)
• Altri autori: AbdullahRosni GeemZong Woo
• 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.
• Titolo autorizzato: Artificial neural network training and software implementation techniques
• ISBN: 1-62257-103-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910957230303321
• Lo trovi qui: Univ. Federico II
• Serie: Computer networks series.; Novinka.