| Autor: |
A. Moopenn, Silvio P. Eberhardt, A. Thakoor |
| Rok vydání: |
2005 |
| Předmět: |
|
| Zdroj: |
Twenty-Second Asilomar Conference on Signals, Systems and Computers. |
| DOI: |
10.1109/acssc.1988.754628 |
| Popis: |
In constructing electronic hardware neural networks, algorithms as well as circuitry must be designed in a manner tolerant of limitations imposed by the implementation medi- um. Two development efforts are described in which hardware and algorithms are designed to operate within space, dynamic range, and noise constraints of analog CMOS VLSI technology. The performance of a single-layer feedback network incorporating simple binary interconnects is extended by using an analog prompt method. A "building block" approach for the design of multilayer feedforward networks is made possible by a new learning algorithm tolerant of hardware limitations. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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