Orders > Conference proceedings > 12th international workshop on systems, signals and image processing
(from Chapter 1: Invited Addresses and Tutorials on Signals, Coding, Systems and Intelligent Techniques)
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Title: |
Implementation of opamps for teaching of electronic neural networks |
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Author(s): |
Stylianos Halkiadis, Nikolaos Chasanagas |
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Address: |
Department of Electrical Engineering, Technological Educational Institution of Chalkida, 34400 Psahna, Evia, Greece shalk @ tee.gr, nchasanagas @ yahoo.com |
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Reference: |
SSIP-SP1, 2005 pp. 427 - 431 |
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Abstract/ Summary |
Laboratory experiments for neural networks usually comprised of software simulators, however participants of engineering courses have diverse background with variable software experience. To avoid learning burdening, engineering laboratory introduction of neural networks is essential. In most of the cases the introductory phase consists of theory, in form of handouts and notes. However hands-on experimental work, could be an added value in simulations study. This paper introduces a two-state hardware circuit consisting of two-processor units made of operational amplifiers (opamps). The system is also supplied with a simple threshhold logic in order to demonstrate the spatial and temporal summing behavior of neurons. The proposed model is comprehensive and easily applicable introducing students to basic knowledge of artificial intelligence. |
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