Propuesta de implementación y simulación de modelos basados en sinapsis dinámica

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