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Castillo Atoche, A., Carrasco Alvarez, R. and Palma Marrufo, O. (2017) An Efficient Systolic Array Grid-Based Structure of the Robust Bayesian Regularization Technique for Realtime Enhanced Imaging in Uncertain Remote Sensing Environment. Journal of Real-Time Image Processing, 13, 783-796.
https://doi.org/10.1007/s11554-014-0441-y

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• TITLE: An Entropy Measurement Method of Quantum Information System under Uncertain Environment

  AUTHORS: Zijing Li, Jiangnan Deng, Bing Zhou, Ying Liu, Zhengying Cai

  KEYWORDS: Entropy Measurement Method, Quantum Information System, Uncertain Environment, Quantum Encryption

  JOURNAL NAME: International Journal of Intelligence Science, Vol.8 No.2, April 30, 2018

  ABSTRACT: Under uncertain environment, it is very difficult to measure the entropy of quantum information system, because there is no effective method to model the randomness. First, different from the traditional classic uncertainty, a quantum uncertain model is proposed to simulate a quantum information system under uncertain environment, and to simplify the entropy measurement of quantum information system. Second, different from the classic random seed under uncertain environment which is often called as pseudo-random number, here the quantum random is employed to provide us a true random model for the entropy of quantum information system. Third, the complex interaction and entangling activity of uncertain factors of quantum information is modeled as quantum binary instead of classic binary, which can help us to evaluate the entropy of uncertain environment, to analyze the entropy divergence in quantum information system. This work presents a non-classic risk factor measurement for quantum information system and a helpful entropy measurement.