Design of neuron-bipolar junction transistor (νBJT) cellular neural network (CNN) structure with multi-neighborhood-layer templates

Wen Cheng Yen*, Chung-Yu Wu

*Corresponding author for this work

Research output: Contribution to conferencePaper

6 Scopus citations

Abstract

A compact and efficient neuron-bipolar junction transistor (νBJT) cellular neural network (CNN) structure with multi-neighborhood-layer templates is proposed and analyzed. Using the proposed structure, the coefficients of the templates with two neighborhood layers are fully realizable. But those with more than two neighborhood layers are constrained. As the demonstrative examples on the applications of the proposed vBJT CNNs, the functions of both de-blurring and muller-lyer arrowhead illusion functions have been successfully realized and verified by HSPICE simulation.

Original languageEnglish
Pages195-200
Number of pages6
StatePublished - 1 Jan 2000
EventProceedings of the 2000 6th IEEE International Workshop on Cellular Neural Network and their Applications (CNNA 2000) - Catania, Italy
Duration: 23 May 200025 May 2000

Conference

ConferenceProceedings of the 2000 6th IEEE International Workshop on Cellular Neural Network and their Applications (CNNA 2000)
CityCatania, Italy
Period23/05/0025/05/00

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    Yen, W. C., & Wu, C-Y. (2000). Design of neuron-bipolar junction transistor (νBJT) cellular neural network (CNN) structure with multi-neighborhood-layer templates. 195-200. Paper presented at Proceedings of the 2000 6th IEEE International Workshop on Cellular Neural Network and their Applications (CNNA 2000), Catania, Italy, .