Abstract
We introduce a novel learning algorithm called multi-core learning (MCL) to construct a neural network for implementing a Boolean link training algorithm (BLTA) and expand-and-truncate learning (ETL). MCL needs a fewer hidden neurons. MCL also needs less number of operations for obtaining the connection weights and thresholds for hidden layer. We illustrate this advantage of our method (over ETL and BLTA) through an example.
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