Neural Smithing

Neural Smithing
Author: Russell Reed
Publisher: MIT Press
Total Pages: 359
Release: 1999-02-17
Genre: Computers
ISBN: 0262527014

Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptrons (MLP). These are the mostly widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition). This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research.

Neural Network Analysis, Architectures and Applications

Neural Network Analysis, Architectures and Applications
Author: A Browne
Publisher: CRC Press
Total Pages: 294
Release: 1997-01-01
Genre: Mathematics
ISBN: 9780750304993

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. It then describes novel architectures and algorithms, including pulse-stream techniques, cellular neural networks, and multiversion neural computing. The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image compression. This final part of the book also provides a case study involving oil spill detection. This book is invaluable for students and practitioners who have a basic understanding of neural computing yet want to broaden and deepen their knowledge of the field.

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Author: Nikola K. Kasabov
Publisher: Marcel Alencar
Total Pages: 581
Release: 1996
Genre: Artificial intelligence
ISBN: 0262112124

Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.

Proceedings of the 2nd International Conference on Communication, Devices and Computing

Proceedings of the 2nd International Conference on Communication, Devices and Computing
Author: Sumit Kundu
Publisher: Springer Nature
Total Pages: 720
Release: 2019-12-16
Genre: Technology & Engineering
ISBN: 9811508291

This book gathers high-quality papers presented at the 2nd International Conference on Communication, Devices & Computing (ICCDC 2019), held at Haldia Institute of Technology from March 14–15, 2019. The papers are divided into three main areas: communication technologies, electronics circuits & devices and computing. Written by students and researchers from around the world, they accurately reflect the global status quo.

Expert Systems

Expert Systems
Author: Cornelius T. Leondes
Publisher: Elsevier
Total Pages: 2125
Release: 2001-09-26
Genre: Computers
ISBN: 0080531458

This six-volume set presents cutting-edge advances and applications of expert systems. Because expert systems combine the expertise of engineers, computer scientists, and computer programmers, each group will benefit from buying this important reference work. An "expert system" is a knowledge-based computer system that emulates the decision-making ability of a human expert. The primary role of the expert system is to perform appropriate functions under the close supervision of the human, whose work is supported by that expert system. In the reverse, this same expert system can monitor and double check the human in the performance of a task. Human-computer interaction in our highly complex world requires the development of a wide array of expert systems. Expert systems techniques and applications are presented for a diverse array of topics including Experimental design and decision support The integration of machine learning with knowledge acquisition for the design of expert systems Process planning in design and manufacturing systems and process control applications Knowledge discovery in large-scale knowledge bases Robotic systems Geograhphic information systems Image analysis, recognition and interpretation Cellular automata methods for pattern recognition Real-time fault tolerant control systems CAD-based vision systems in pattern matching processes Financial systems Agricultural applications Medical diagnosis

Artificial Neural Networks-Icann '97

Artificial Neural Networks-Icann '97
Author: Wulfram Gerstner
Publisher: Springer Science & Business Media
Total Pages: 1300
Release: 1997-09-29
Genre: Computers
ISBN: 9783540636311

Content Description #Includes bibliographical references and index.

Artificial Neural Networks - ICANN 2008

Artificial Neural Networks - ICANN 2008
Author: Vera Kůrková
Publisher: Springer Science & Business Media
Total Pages: 1053
Release: 2008-08-25
Genre: Computers
ISBN: 3540875352

This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008. The 200 revised full papers presented were carefully reviewed and selected from more than 300 submissions. The first volume contains papers on mathematical theory of neurocomputing, learning algorithms, kernel methods, statistical learning and ensemble techniques, support vector machines, reinforcement learning, evolutionary computing, hybrid systems, self-organization, control and robotics, signal and time series processing and image processing.

Advances in Neural Networks - ISNN 2008

Advances in Neural Networks - ISNN 2008
Author: Fuchun Sun
Publisher: Springer
Total Pages: 876
Release: 2008-09-20
Genre: Computers
ISBN: 3540877347

The two volume set LNCS 5263/5264 constitutes the refereed proceedings of the 5th International Symposium on Neural Networks, ISNN 2008, held in Beijing, China in September 2008. The 192 revised papers presented were carefully reviewed and selected from a total of 522 submissions. The papers are organized in topical sections on computational neuroscience; cognitive science; mathematical modeling of neural systems; stability and nonlinear analysis; feedforward and fuzzy neural networks; probabilistic methods; supervised learning; unsupervised learning; support vector machine and kernel methods; hybrid optimisation algorithms; machine learning and data mining; intelligent control and robotics; pattern recognition; audio image processinc and computer vision; fault diagnosis; applications and implementations; applications of neural networks in electronic engineering; cellular neural networks and advanced control with neural networks; nature inspired methods of high-dimensional discrete data analysis; pattern recognition and information processing using neural networks.

Metaheuristic Computation with MATLAB®

Metaheuristic Computation with MATLAB®
Author: Erik Cuevas
Publisher: CRC Press
Total Pages: 281
Release: 2020-09-14
Genre: Computers
ISBN: 1000096513

Metaheuristic algorithms are considered as generic optimization tools that can solve very complex problems characterized by having very large search spaces. Metaheuristic methods reduce the effective size of the search space through the use of effective search strategies. Book Features: Provides a unified view of the most popular metaheuristic methods currently in use Includes the necessary concepts to enable readers to implement and modify already known metaheuristic methods to solve problems Covers design aspects and implementation in MATLAB® Contains numerous examples of problems and solutions that demonstrate the power of these methods of optimization The material has been written from a teaching perspective and, for this reason, this book is primarily intended for undergraduate and postgraduate students of artificial intelligence, metaheuristic methods, and/or evolutionary computation. The objective is to bridge the gap between metaheuristic techniques and complex optimization problems that profit from the convenient properties of metaheuristic approaches. Therefore, engineer practitioners who are not familiar with metaheuristic computation will appreciate that the techniques discussed are beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas.