Title, Neural Computing: Theory and Practice. Author, Philip D. Wasserman. Publisher, Van Nostrand Reinhold. ISBN, X, Following up where Neural Computing: Theory and Practice left off, this guide explains diverse high-performance paradigms for artificial neural networks ( ANNs). 21 May Neural computing. by Philip D. Wasserman. Publication date Topics Neural computers. Publisher Van Nostrand Reinhold. Collection.
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Sunit Sharma marked it as to-read Nov 14, Explanations of the paradigms are program-oriented and are written in algorithmic form. Ivette Miramontes marked it as to-read Feb 23, No trivia or quizzes yet.
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Manimaran marked it as to-read Jan 03, This book for nonspecialists clearly explains major algorithms and demystifies the rigorous math involved in neural networks. Paradigms that are still in the research stage, but offer great potential, are also discussed. Self-contained chapters cover field theory methods, including Nestor’s restricted coulomb energy system; probabilistic neural neurzl, which can increase training speed by orders of magnitude; genetic algorithms that mimic biological evolution; sparse neural computing theory and practice by philip d.wasserman memory, a powerful associative memory paradigm, which is compatible with VLSI implementation; fuzzy logic methods that are finding widespread application in control systems; neural engineering, including a set of techniques for designing, training, and applying artificial neural systems to real-world problems; and additional chapters cover basis function methods, chaos, and automatic control.
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Vasavi Nagichetty marked it as to-read Mar 04, Psd added it Apr 20, Preview — Neural Computing by Philip D. Washta Kapoor marked it as to-read Feb 15, neural computing theory and practice by philip d.wasserman Noni marked it as to-read .dwasserman 14, Surbhi marked it as to-read Nov 14, Advanced Methods in Neural Computing meets the reference needs of electronics engineers, d.sasserman systems engineers, programmers, and others in scientific disciplines.
Theory and Practice left off, this guide explains diverse high-performance paradigms for artificial neural networks ANNs that function effectively in real-world situations.
There are no discussion topics on this book yet. Murali added it Jul 22, Oleg Potapov is currently reading it Jun 23, Nikz Murali marked it as to-read Nov 21, Rossdavidh rated it really liked it Aug 21, Ashil Kurian marked it as to-read Apr 25, Maria Vijoy rated it it was amazing Dec 05, Theory and Practice 3. Want to Read saving…. Alexandr marked it as to-read Dec 18,