Ponencia
A Model for VLSI implementation of CNN image processing chips using current-mode techniques
Autor/es | Espejo Meana, Servando Carlos
Rodríguez Vázquez, Ángel Benito Domínguez Castro, Rafael Linares Barranco, Bernabé Huertas Díaz, José Luis |
Departamento | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo |
Fecha de publicación | 1993 |
Fecha de depósito | 2020-03-11 |
Publicado en |
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ISBN/ISSN | 0-7803-1281-3 0271-4310 |
Resumen | A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation than previous models. Current-mode building blocks are presented for the design of CMOS image preprocessing chips (feature ... A new Cellular Neural Network model is proposed which allows simpler and faster VLSI implementation than previous models. Current-mode building blocks are presented for the design of CMOS image preprocessing chips (feature extraction, noise filtering , compound component detection, etc.) using the cellular neural network paradigm. Area evaluation for the new model shows a reduction off about 50% as compared to the use of current-mode techniques with conventional models. Experimental measurements of CMOS prototypes designed in a 1.6 μm n-well double-metal single-poly technology are reported. |
Cita | Espejo Meana, S.C., Rodríguez Vázquez, Á.B., Domínguez Castro, R., Linares Barranco, B. y Huertas Díaz, J.L. (1993). A Model for VLSI implementation of CNN image processing chips using current-mode techniques. En IEEE International Symposium on Circuits and Systems (970-973), Chicago, USA: Institute of Electrical and Electronics Engineers. |
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