Neural Networks Theory
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| Author | : Alexander I. Galushkin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 396 |
| Release | : 2007-10-29 |
| Genre | : Technology & Engineering |
| ISBN | : 3540481257 |
This book, written by a leader in neural network theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization. It details more than 40 years of Soviet and Russian neural network research and presents a systematized methodology of neural networks synthesis. The theory is expansive: covering not just traditional topics such as network architecture but also neural continua in function spaces as well.
| Author | : Xingui He |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 240 |
| Release | : 2010-07-05 |
| Genre | : Computers |
| ISBN | : 3540737626 |
For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.
| Author | : Daniel A. Roberts |
| Publisher | : Cambridge University Press |
| Total Pages | : 473 |
| Release | : 2022-05-26 |
| Genre | : Computers |
| ISBN | : 1316519333 |
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
| Author | : Michael A. Arbib |
| Publisher | : MIT Press |
| Total Pages | : 1328 |
| Release | : 2003 |
| Genre | : Neural circuitry |
| ISBN | : 0262011972 |
This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).
| Author | : Michael A. Arbib |
| Publisher | : MIT Press (MA) |
| Total Pages | : 1118 |
| Release | : 1998 |
| Genre | : Computers |
| ISBN | : 9780262511025 |
Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does the brain work? How can we build intelligent machines? While many books discuss limited aspects of one subfield or another of brain theory and neural networks, the Handbook covers the entire sweep of topics—from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks. Expository material makes the book accessible to readers with varied backgrounds while still offering a clear view of the recent, specialized research on specific topics.
| Author | : Seyedali Mirjalili |
| Publisher | : Springer |
| Total Pages | : 164 |
| Release | : 2018-06-26 |
| Genre | : Technology & Engineering |
| ISBN | : 3319930257 |
This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
| Author | : Martin Anthony |
| Publisher | : Cambridge University Press |
| Total Pages | : 405 |
| Release | : 1999-11-04 |
| Genre | : Computers |
| ISBN | : 052157353X |
This work explores probabilistic models of supervised learning problems and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, the authors develop a model of classification by real-output networks, and demonstrate the usefulness of classification...
| Author | : K. I. Diamantaras |
| Publisher | : Wiley-Interscience |
| Total Pages | : 282 |
| Release | : 1996-03-08 |
| Genre | : Computers |
| ISBN | : |
Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectural aspects of principal component neural networks. Using a unified formulation, the authors present neural models performing PCA from the Hebbian learning rule and those which use least squares learning rules such as back-propagation. Examines the principles of biological perceptual systems to explain how the brain works. Every chapter contains a selected list of applications examples from diverse areas.
| Author | : John A. Hertz |
| Publisher | : CRC Press |
| Total Pages | : 352 |
| Release | : 2018-03-08 |
| Genre | : Science |
| ISBN | : 0429968213 |
Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.
| Author | : Puyin Liu |
| Publisher | : World Scientific |
| Total Pages | : 400 |
| Release | : 2004 |
| Genre | : Computers |
| ISBN | : 9789812794215 |
This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering. Contents: Fuzzy Neural Networks for Storing and Classifying; Fuzzy Associative Memory OCo Feedback Networks; Regular Fuzzy Neural Networks; Polygonal Fuzzy Neural Networks; Approximation Analysis of Fuzzy Systems; Stochastic Fuzzy Systems and Approximations; Application of FNN to Image Restoration. Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing."
