This textbook is intended for a first-year graduate course on artificial neural networks. It assumes no prior background in the subject and is directed to MS students in electrical engineering, computer science and related fields, with background in at least one programming language or in a programm
Principles of artificial neural networks
โ Scribed by Daniel Graupe
- Publisher
- World Scientific
- Year
- 2007
- Tongue
- English
- Leaves
- 320
- Series
- Advanced series on circuits and systems 6
- Edition
- 2nd ed
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.
๐ SIMILAR VOLUMES
Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. <P> This volume covers the basic theory and architecture
The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural networ