Optimal Training Parameters and Hidden Layer Neuron Number of TwoLayer Perceptron for Generalised Scaled Object Classification Problem
Abstract
The research is focused on optimising twolayer perceptron for generalised scaled object classification problem. The optimisation criterion is minimisation of inaccuracy. The inaccuracy depends on training parameters and hidden layer neuron number. After its statistics is accumulated, minimisation is executed by a numerical search. Perceptron is optimised additionally by extra training. As it is done, the classification error percentage does not exceed 3 % in case of the worst scale distortion.
Keywords: 
Extra pass training; optimization; scalingproof classifier; twolayer perceptron

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References
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