SciELO - Scientific Electronic Library Online

 
vol.14 número55Diseño de una red inalámbrica para aplicaciones de telemedicinaModelado y simulación en pscad de celdas fotovoltaicas índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

Compartir


Universidad, Ciencia y Tecnología

versión impresa ISSN 1316-4821versión On-line ISSN 2542-3401

Resumen

OLMEDO, Alvaro  y  CHANG, Oscar. Proposal for implementation and simulation of models based on dynamic sinapse. uct [online]. 2010, vol.14, n.55, pp.119-127. ISSN 1316-4821.

Some problems in the field of non-stationary and highly non-lineal sign processing, such as voice recognition, have not been solved by traditional neural network. This proposal for implementation and simulation of a dynamic sinapse is offered to have a background for the biological neuron, specifically depression and facilitation phenomena ocurred in the sinaptic knot as a product of pulse neuronal feedback giving these cells the capacity of self modulating, that is, changing the pulse sequence that excite this biological structure and also giving man the ability to recognize things. To test the model, some timedepending sequences like Spanish spoken words were experimented. They were processed through a Double Delta modulation to emulate the impulses that excite human cells. This study shows the model efficiency to answer with a different pulse sequence to each input sequence. It was verified that the answers are similar for equal sequences (words) no matter who pronunces them. This is the most important fact and there is no doubt it will contribuye to develop classification and recognition systems in future studies

Palabras clave : Dynamic Neural Networks; Dynamic Sinapse; Voice Recognition; Simulation.

        · resumen en Español     · texto en Español

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons