Information Sciences—Intelligent Systems: An International Journal
Information Sciences—Informatics and Computer Science: An International Journal
Image Compression by Layered Quantum Neural Networks
Neural Processing Letters
Associative Memory Based Image and Object Recognition by Quantum Holography
Open Systems & Information Dynamics
Qubit neural network and its learning efficiency
Neural Computing and Applications
An Examination of Qubit Neural Network in Controlling an Inverted Pendulum
Neural Processing Letters
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The storage capacity of the conventional neural network is 0.14 times of the number of neurons (P=0.14N). Due to the huge difficulty in recognizing large number of images or patterns, researchers are looking for new methods at all times. Quantum Neural Network (QNN), which is a young and outlying science built upon the combination of classical neural network and quantum computing, is a candidate to solve this problem.This paper presents Quantum Probability Distribution Network (QPDN) whose elements of the storage matrix are distributed in a probabilistic way on the base of quantum linear superposition and applies QPDN on image recognition. Contrasting to the conventional neural network, the storage capacity of the QPDN is increased by a factor of 2N, where N is the number of neurons. Besides, the case analysis and simulation tests have been carried out for the recognition of images in this paper, and the result indicates that QPDN can recognize the images or patterns effectively and its working process accords with quantum evolvement process