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Principles of Neurocomputing for Science and Engineering by Fredric M. Ham, Ivica Kostanic, Frederic M Ham is a book available to read on EtoBox.

What is Principles of Neurocomputing for Science and Engineering about?

Principles Of Neurocomputing For Science And Engineering Is A Textbook Intended For Individuals Who Want To Understand The Underlying Principles Of Artificial Neural Networks For Neurocomputing And For Those Who Want To Be Able To Apply Various Neurocomputing Techniques To Solve Real-world Problems In Science And Engineering. Neurocomputing Can Be Applied To Problems Such As Pattern Recognition, Optimization, Event Classification, Control And Identification Of Nonlinear Systems, And Statistical Analysis - Just To Name A Few. This Book Is Intended For A Course In Neural Networks.--jacket. 1. Introduction To Neurocomputing -- 2. Fundamental Neurocomputing Concepts -- 3. Mapping Networks -- 4. Self-organizing Networks -- 5. Recurrent Networks And Temporal Feedforward Networks -- 6. Neural Networks For Optimization Problems -- 7. Solving Matrix Algebra Problems With Neural Networks -- 8. Solution Of Linear Algebraic Equations Using Neural Networks -- 9. Statistical Methods Using Neural Networks -- 10. Identification, Control, And Estimation Using Neural Networks -- App. A. Mathematical Foundation For Neurocomputing. Frederic M. Ham, Ivica Kostanic. Includes Bibliographical References A

Author

Fredric M. Ham, Ivica Kostanic, Frederic M Ham

Publisher

McGraw-Hill Science/Engineering/Math

Published

2001

Language

EN

ISBN

9780071181617

Subjects

Computer Science, Engineering, Mathematics