Neural Network Systems Techniques and Applications: Algorithms and Architectures 1 by Cornelius T. Leondes read ebook DJV, TXT, MOBI
9780124438613 012443861X A treatment of algorithms and architectures for the realization of neural network systems. This volume presents techniques and methods in numerous areas of this subject and covers neural network systems structures for achieving effective systems. It includes: radial basis function networks; the expand-and-truncate learning algorithm for the synthesis of three-layer threshold networks; weight initialization; Hamming and Hopfield neural networks; discrete time synchronous multilevel neural systsm with reduced VLSI demands; probabilistic design techniques; time-based techniques; techniqeus for reducing physical realization requirements; and applications to finite constraint problems., This volume is the first diverse and comprehensive treatment of algorithms and architectures for the realization of neural network systems. It presents techniques and diverse methods in numerous areas of this broad subject. The book covers major neural network systems structures for achieving effective systems, and illustrates them with examples. this volume includes Radial Basis Function networks, the Expand-and-Truncate Learning algorithm for the synthesis of Three-Layer Threshold Networks, weight initialization, fast and efficient variants of Hamming and Hopfield neural networks, discrete time synchronous multilevel neural systems with reduced VLSI demands, probabilistic design techniques, time-based techniques, techniques for reducing physical realization requirements, and applications to finite constraint problems. a unique and comprehensive reference for a broad array of algorithms and architectures, this book will be of use to practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering.
9780124438613 012443861X A treatment of algorithms and architectures for the realization of neural network systems. This volume presents techniques and methods in numerous areas of this subject and covers neural network systems structures for achieving effective systems. It includes: radial basis function networks; the expand-and-truncate learning algorithm for the synthesis of three-layer threshold networks; weight initialization; Hamming and Hopfield neural networks; discrete time synchronous multilevel neural systsm with reduced VLSI demands; probabilistic design techniques; time-based techniques; techniqeus for reducing physical realization requirements; and applications to finite constraint problems., This volume is the first diverse and comprehensive treatment of algorithms and architectures for the realization of neural network systems. It presents techniques and diverse methods in numerous areas of this broad subject. The book covers major neural network systems structures for achieving effective systems, and illustrates them with examples. this volume includes Radial Basis Function networks, the Expand-and-Truncate Learning algorithm for the synthesis of Three-Layer Threshold Networks, weight initialization, fast and efficient variants of Hamming and Hopfield neural networks, discrete time synchronous multilevel neural systems with reduced VLSI demands, probabilistic design techniques, time-based techniques, techniques for reducing physical realization requirements, and applications to finite constraint problems. a unique and comprehensive reference for a broad array of algorithms and architectures, this book will be of use to practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering.