A Novel Structure Design and Training Algorithm for Quantum Neural Network

In the structure of original Quantum Neural Network (QNN), only multi-sigmoid transfer function is adopted. Besides that, due to the conflict of the two objective functions in original training algorithm, the training process converges slowly and presents constant variation. In this paper, the QNN with multi-tan-sigmoid transfer function and a novel training algorithm which combines the two objective functions are proposed. Experimental results demonstrate the effectiveness of the structure improvement and the new training algorithm. Streszczenie. W oryginalnym algorytmie kwantowej sieci neuronowej QNN tylko multisigmoidalna funkcja przejścia jest wykorzystywana. W pracy zaprezentowano siec z multi-tan-sigmoidalną funkcją przejścia z nowym algorytmem uczenia. (Nowa struktura i algorytm uczenia w kwantowej sieci neuronowej)