A CMOS Analog Two-Layer Full Signal Range Cellular Neural Network for Image Filtering

• Fabian Souza de Andrade UFBA
• Ana Isabela Araújo Cunha UFBA
• Edson Pinto Santana UFBA
• Ygor Oliveira da Guarda Souza UFBA

Resumo

This work presents the training and realization of a CMOS analog two-layer FSR CNN obtained through the extension of an existing one-layer version. A genetic algorithm has been developed for the learning process and has been applied to the determination of templates parameters in a gray-scale image filtering task. Networks implementing first order Butterworth spatial filters have been simulated and the results are compared to its ideal model and FFT computations; allowing to validate the proposed learning process and circuit applicability.

Palavras-chave: Low pass filters, Image filtering, Training, Integrated circuit modeling, Computer architecture, Computational modeling