03120nam 22006014a 450 991078407060332120230124182055.01-281-12170-39786611121709981-277-057-7(CKB)1000000000334129(EBL)312337(OCoLC)648316923(SSID)ssj0000227284(PQKBManifestationID)11947087(PQKBTitleCode)TC0000227284(PQKBWorkID)10264791(PQKB)10433342(MiAaPQ)EBC312337(WSP)00006429(Au-PeEL)EBL312337(CaPaEBR)ebr10188769(CaONFJC)MIL112170(EXLCZ)99100000000033412920080102d2007 uy 0engurcn|||||||||txtccrPrinciples of artificial neural networks[electronic resource] /Daniel Graupe2nd ed.Singapore ;Hackensack, N.J. World Scientificc20071 online resource (320 p.)Advanced series on circuits and systems ;vol. 6Description based upon print version of record.981-270-624-0 Includes bibliographical references (p. 291-297) and indexes.Acknowledgments; Preface to the First Edition; Preface to the Second Edition; Contents; Chapter 1. Introduction and Role of Artificial Neural Networks; Chapter 2. Fundamentals of Biological Neural Networks; Chapter 3. Basic Principles of ANNs and Their Early Structures; Chapter 4. The Perceptron; Chapter 5. The Madaline; Chapter 6. Back Propagation; Chapter 7. Hopeld Networks; Chapter 8. Counter Propagation; Chapter 9. Adaptive Resonance Theory; Chapter 10. The Cognitron and the Neocognitron; Chapter 11. Statistical Training; Chapter 12. Recurrent (Time Cycling) Back Propagation NetworksChapter 13. Large Scale Memory Storage and Retrieval (LAMSTAR) Network Problems; References; Author Index; Subject IndexThe book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengthAdvanced series on circuits and systems ;v. 6.Neural networks (Computer science)Neural networks (Computer science)006.3/2Graupe Daniel14109MiAaPQMiAaPQMiAaPQBOOK9910784070603321Principles of artificial neural networks3696591UNINA