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- W2770763876 abstract "Achieving low cost learning with reliable accuracy is one of the important goals to achieve intelligent machines to save time, energy and perform learning process over limited computational resources machines. In this paper, we propose an efficient algorithm for a perceptron neural network inspired by quantum computing composite from a single neuron to classify inspirable linear applications after a single training iteration O(1). The algorithm is applied over a real world data set and the results are outer performs the other state-of-the art algorithms." @default.
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- W2770763876 date "2017-01-01" @default.
- W2770763876 modified "2023-09-28" @default.
- W2770763876 title "Low-cost autonomous perceptron neural network inspired by quantum computation" @default.
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- W2770763876 doi "https://doi.org/10.1063/1.5012145" @default.
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