Analog Circuit-Design And Implementation Of An Adaptive Resonance Theory (Art) Neural-Network Architecture

    Authors

    C. S. Ho; J. J. Liou; M. Georgiopoulos; G. L. Heileman;C. Christodoulou

    Comments

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    Abbreviated Journal Title

    Int. J. Electron.

    Keywords

    PATTERN-RECOGNITION; Engineering, Electrical & Electronic

    Abstract

    An analogue circuit implementation is presented for an adaptive resonance theory neural network architecture, called the augmented ART-1 neural network (AARTI-NN). The AARTI-NN is a modification of the popular ARTI-NN, developed by Carpenter and Grossberg, and it exhibits the same behaviour as the ART1-NN. The AART1-NN is a real-time model, and has the ability to classify an arbitrary set of binary input patterns into different clusters. The design of the AARTI-NN circuit is based on a set of coupled nonlinear differential equations that constitute the AARTI-NN model. The circuit is implemented by utilizing analogue electronic components such as operational amplifiers, transistors, capacitors, and resistors. The implemented circuit is verified using the PSpice circuit simulator, running on Sun workstations. Results obtained from the PSpice circuit simulation compare favourably with simulation results produced by solving the differential equations numerically. The prototype system developed here can be used as a building block for larger AARTI-NN architectures, as well as for other types of ART architectures that involve the AARTI-NN model.

    Journal Title

    International Journal of Electronics

    Volume

    76

    Issue/Number

    2

    Publication Date

    1-1-1994

    Document Type

    Article

    Language

    English

    First Page

    271

    Last Page

    291

    WOS Identifier

    WOS:A1994MX99600010

    ISSN

    0020-7217

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