M.W. Benson (Canada) and J. Hu (USA)
neural networks, self-organizing, parallel, asynchronous,optimization
An asynchronous algorithm is formulated for generating self organizing maps that arise from the minimization of an energy function. Results using a simulations along with ex periments using a shared memory parallel computer show the asynchronous approach to be effective. Successful re sults are also demonstrated with an asynchronous variation on the Kohonen self-organizing map algorithm where no global energy function is present. A partitioning of the weight array so each processor is responsible for a small part of this array proves effective and improves the parallel efficiency of the asynchronous approach.
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