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Neural Networks and Analog Computation: Beyond the Turing Limit - Progress in Theoretical Computer Science Hava T. Siegelmann Softcover Reprint of the Original 1st Ed. 1999 edition
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Neural Networks and Analog Computation: Beyond the Turing Limit - Progress in Theoretical Computer Science
Hava T. Siegelmann
The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.
181 pages, biography
| Mediji | Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru) |
| Izlaists | 2012. gada 21. oktobris |
| ISBN13 | 9781461268758 |
| Izdevēji | Springer-Verlag New York Inc. |
| Lapas | 181 |
| Izmēri | 155 × 235 × 11 mm · 290 g |
| Valoda | Angļu |
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