Chapter 1: Invited Addresses and Tutorials on Signals, Coding,
  Systems and Intelligent Techniques

Title: Implementation of opamps for teaching of electronic neural networks

Author(s): Stylianos Halkiadis, Nikolaos Chasanagas

Address: Department of Electrical Engineering, Technological Educational Institution of Chalkida, 34400 Psahna, Evia, Greece | Department of Electrical Engineering, Technological Educational Institution of Chalkida, 34400 Psahna, Evia, Greece

Reference: 12th International Workshop on Systems, Signals and Image Processing pp. 427 - 431

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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