Real-time associative recognizing system for binary patterns

Lulin Chen; Lin Lin; Ruli Wang

doi:10.1117/12.140056

16 September 1992 Real-time associative recognizing system for binary patterns

Lulin Chen, Lin Lin, Ruli Wang

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.140056
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

This presentation describes the real-time associative recognizing system based on neural network technology for distortion-invariant pattern recognition. The system consists of two cascaded parts, i.e., an improved MADALINE invariant net with local connecting structure, and a feed-forward layered net of probabilistic logic neuron (PLN). The simple learning algorithm is proposed for the system. General-purpose RAMs are major parts of the system so that real-time processing is available.

Citation Download Citation

Lulin Chen, Lin Lin, and Ruli Wang "Real-time associative recognizing system for binary patterns", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140056

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