Kohonen Feature Map Associative Memory with Area Representation

Kohonen Feature Map Associative Memory with Refractoriness based on Area Representation

Variable-Sized Kohonen Feature Map Probabilistic Associative Memory

This paper presents a Variable-sized Kohonen Feature Map Probabilistic Associative Memory for Sequential Patterns (VKFMPAM-SP) which can realize successive (additional) learning for sequential patterns. In the proposed model, since the connection weights of the neurons which are centers of the area corresponding to the stored data are fixed, new patterns can be memorized without destroying memo...

On-line recognition of handwritten Arabic characters using a Kohonen neural network

Neural networks have been applied to various pattern classification and recognition problems for their learning ability, discrimination power, and generalization ability. The neural network most referenced in the pattern recognition literature are the multi-layer perceptron, the Kohonen associative memory and the Capenter-Grossberg ART network. The Kohonen memory runs an unsupervised clustering...

Reinforcement Learning using Kohonen Feature Map Probabilistic Associative Memory based on Weights Distribution

The reinforcement learning is a sub-area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward(Sutton & Barto, 1998). Reinforcement learning algorithms attempt to find a policy that maps states of the world to the actions the agent ought to take in those states. Temporal Difference (TD) learning is one of the re...

Towards an Information Density Measure for Neural Feature Maps

Many neural models have been suggested for the development of feature maps in cortical areas. Undoubtedly the most popular model is the Kohonen self-organizing map (SOM). Once the map has been learned, this network uses a competitive winner-take-all (WTA) approach to choose a singlèbest' output neuron on a (typically) 2D grid for each presented input pattern. Cortical maps in biological organis...