Nature has evolved computing engines whose intelligence and natural abilities are unrivaled by modern computers. To match Mother Nature's abilities, we must overcome the same difficulties faced by natural systems, and we must learn to perform reliable computing with unreliable components. Steps in this direction are being taken by several groups at the Applied Physics Laboratory and at The Johns Hopkins University Department of Electrical and Computer Engineering. The purpose of the work is twofold: (1) to explore algorithms based on physical and neural models of computation and (2) to develop useful applications. We describe the basic approach and an experimental electronic neural network for the decompression of one-dimensional signals.
|Original language||English (US)|
|Number of pages||4|
|Journal||Johns Hopkins APL Technical Digest (Applied Physics Laboratory)|
|State||Published - Jan 1 1994|
ASJC Scopus subject areas
- Physics and Astronomy(all)