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This paper proposes two main techniques for reduce computational complexity on artificial neural networks, using piecewise linear activation function, and support vector machines built on a probability based binary tree. These methods are compared with well-known classifiers based on the computational complexity, correct rate and time taken to process the required information. The results show that probability based binary tree SVM has an equivalent recognition rate and is faster than ANNs.
Date of Conference: 12-14 March 2008