Now showing items 1-5 of 5
Aprendizaje No Supervisado (Aprendizaje Asociativo)
It gives an introduction to associative learning using Hebb's postulate of learning networks belonging to unsupervised.
Aplicaciones de Redes Neuronales e Inspiracióm Biológica
This presentation will raise a number of areas where they apply different neural network paradigms. We describe the biological model of a neuron, as well as the basics of neuron.
Introducción a las Redes Neuronales
This presentation describes a brief history of Neural Networks (RN), are some definitions of RN, and their advantages and disadvantages, in order to identify the basics and fundamentals of neural networks
Mapa Auto Organizados
It describes the characteristics of self-organizing maps, the learning rule, the training algorithm, in order to solve classification problems.
We describe the Perceptron model, history, characteristics, training algorithm for solving classification problems, worked examples are also presented, as well as the limitations of this type of network.