Synopses & Reviews
Develop New Insight into the Behavior of Adaptive SystemsThis one-of-a-kind interactive book and CD-ROM will help you develop a better understanding of the behavior of adaptive systems. Developed as part of a project aimed at innovating the teaching of adaptive systems in science and engineering, it unifies the concepts of neural networks and adaptive filters into a common framework. It begins by explaining the fundamentals of adaptive linear regression and builds on these concepts to explore pattern classification, function approximation, feature extraction, and time-series modeling/prediction. The text is integrated with the industry standard neural network/adaptive system simulator NeuroSolutions. This allows the authors to demonstrate and reinforce key concepts using over 200 interactive examples. Each of these examples is 'live,' allowing the user to change parameters and experiment first-hand with real-world adaptive systems. This creates a powerful environment for learning through both visualization and experimentation. Key Features of the Text
- The text and CD combine to become an interactive learning tool.
- Emphasis is on understanding the behavior of adaptive systems rather than mathematical derivations.
- Each key concept is followed by an interactive example.
- Over 200 fully functional simulations of adaptive systems are included.
- The text and CD offer a unified view of neural networks, adaptive filters, pattern recognition, and support vector machines.
- Hyperlinks allow instant access to keyword definitions, bibliographic references, equations, and advanced discussions of concepts.
The CD-ROM Contains:
- A complete, electronic version of the text in hypertext format
- NeuroSolutions, an industry standard, icon-based neural network/adaptive system simulator
- A tutorial on how to use NeuroSolutions
- Additional data files to use with the simulator
"An innovative approach to describing neurocomputing and adaptive learning systems from a perspective which unifies classical linear adaptive systems approaches with the modern advances in neural networks. It is rich in examples and practical insight."
—James Zeidler, University of California, San Diego
Synopsis
Neural networks have become one of the most sophisticated applications in use today by engineers and others in a myriad of applications such as cellular networks, financial analysis, stock market analysis, traffic coordination, etc. In this new approach, the authors blend neurocomputing theory with the power of a software simulator to underscore synergisms between the conceptual equations and their behavior in practical neural systems.
Synopsis
Ein einzigartiger und innovativer Ansatz zur Vermittlung von Kenntnissen ber adaptive und neuronale Netze Der Leser experimentiert mit realen Datens tzen und lernt so, das Verhalten der Netzwerke intuitiv einzusch tzen. Als interaktives Lehr- und Lernmittel bietet das Buch ber 200 voll funktionsf hige Simulationen mit ausf hrlichen Arbeitsanleitungen - ideal auch zum Selbststudium Die elektronische Version des Buches enth lt neben dem vollst ndigen Text interessante Extras. (01/00)
Synopsis
Develop New Insight into the Behavior of Adaptive Systems This one-of-a-kind interactive book and CD-ROM will help you develop a better understanding of the behavior of adaptive systems. Developed as part of a project aimed at innovating the teaching of adaptive systems in science and engineering, it unifies the concepts of neural networks and adaptive filters into a common framework. It begins by explaining the fundamentals of adaptive linear regression and builds on these concepts to explore pattern classification, function approximation, feature extraction, and time-series modeling/prediction. The text is integrated with the industry standard neural network/adaptive system simulator NeuroSolutions. This allows the authors to demonstrate and reinforce key concepts using over 200 interactive examples. Each of these examples is 'live,' allowing the user to change parameters and experiment first-hand with real-world adaptive systems. This creates a powerful environment for learning through both visualization and experimentation. Key Features of the Text
* The text and CD combine to become an interactive learning tool.
* Emphasis is on understanding the behavior of adaptive systems rather than mathematical derivations.
* Each key concept is followed by an interactive example.
* Over 200 fully functional simulations of adaptive systems are included.
* The text and CD offer a unified view of neural networks, adaptive filters, pattern recognition, and support vector machines.
* Hyperlinks allow instant access to keyword definitions, bibliographic references, equations, and advanced discussions of concepts.
The CD-ROM Contains:
* A complete, electronic version of the text in hypertext format
* NeuroSolutions, an industry standard, icon-based neural network/adaptive system simulator
* A tutorial on how to use NeuroSolutions
* Additional data files to use with the simulator
"An innovative approach to describing neurocomputing and adaptive learning systems from a perspective which unifies classical linear adaptive systems approaches with the modern advances in neural networks. It is rich in examples and practical insight." -James Zeidler, University of California, San Diego
Synopsis
An innovative approach to describing neurocomputing and adaptive learning systems from a perspective which unifies classical linear adaptive systems approaches with the modern advances in neural networks. It is rich in examples and practical insight. -James Zeidler, University of California, San Diego
About the Author
Jose C. Principe, University of FloridaNeil R. Euliano and W. Curt Lefebvre, both of NeuroDimension, Inc.
Table of Contents
Data Fitting with Linear Models.
Pattern Recognition.
Multilayer Perceptrons.
Designing and Training MLPs.
Function Approximation with MLPs, Radial Basis Functions, and Support Vector Machines.
Hebbian Learning and Principal Component Analysis.
Competitive and Kohonen Networks.
Principles of Digital Signal Processing.
Adaptive Filters.
Temporal Processing with Neural Networks.
Training and Using Recurrent Networks.
Appendices.
Glossary.
Index.