A Unitary Weights Based One-Iteration Quantum Perceptron Algorithm for Non-Ideal Training Sets

In order to solve the problem of non-ideal training sets (i.e., the less-complete or over-complete sets) and implement one-iteration learning, a novel efficient quantum perceptron algorithm based on unitary weights is proposed, where the singular value decomposition of the total weight matrix from t...

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Үндсэн зохиолчид:	Wenjie Liu, Peipei Gao, Yuxiang Wang, Wenbin Yu, Maojun Zhang
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	IEEE 2019-01-01
Цуврал:	IEEE Access
Нөхцлүүд:	Quantum perceptron unitary weight one-iteration learning non-ideal training set singular value decomposition universal quantum gates
Онлайн хандалт:	https://ieeexplore.ieee.org/document/8631025/
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