The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.
Contents
- Preface
- Acknowledgments
- Introduction
- Learning Methods
- Data Normalization
- Data Collection, Preparation, Labeling, and Input Coding
- Output Coding
- Post-Processing
- Supervised Training Methods
- Unsupervised Training Methods
- Recurrent Neural Networks
- A Plethora of Applications
- Dealing with Limited Amounts of Data
- Appendix A: The Feedforward Neural Network
- Appendix B: Feature Saliency
- Appendix C: Matlab Code for Various Neural Networks
- Appendix D: Glossary of Terms
- References
- Index
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Book Description PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # CA-9780819459879
Book Description Paperback. Condition: Brand New. illustrated edition. 180 pages. 9.75x7.00x0.50 inches. In Stock. Seller Inventory # __0819459879
Book Description PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # CA-9780819459879