Resolution Method

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Li Zou - One of the best experts on this subject based on the ideXlab platform.

  • FUZZ-IEEE - A Resolution Method for linguistic truth-valued intuitionistic fuzzy first-order logic
    2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
    Co-Authors: Lin Xiao, Jia Meng, Shifei Ding, Li Zou
    Abstract:

    This research aims at finding a way to deal with the uncertain problem which has both positive evidence and negative evidence at the same time. Based on the linguistic truth-valued lattice implication algebra, we establish six-element linguistic truth-valued linguistic intuitionistic fuzzy first-order logic system. Subsequently, we present a Resolution Method of six-element linguistic truth-valued linguistic intuitionistic fuzzy first-order logic (6LTV_IFFL) and prove the soundness of it. Meanwhile, the step of Resolution Method of 6LTV_IFFL is given.

  • Qualitative fuzzy logic system and its Resolution Method
    Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826), 1
    Co-Authors: Xin Liu, Li Zou
    Abstract:

    Using Kripke-style semantic, a kind of qualitative fuzzy proposition logic system is introduced. In this system, the true value of a qualitative fuzzy proposition is depended on the equivalence relation of the possible worlds. It is extension of the classical fuzzy proposition logic. Then some properties of this system and the Resolution Method of the qualitative fuzzy proposition logic are discussed.

  • Resolution Method of Linguistic Truth-valued Propositional Logic
    2005 International Conference on Neural Networks and Brain, 1
    Co-Authors: Li Zou, Xin Liu
    Abstract:

    The linguistic hedge in the truth value of a proposition can strengthen or weaken the degree of the truth value. The truth value of a proposition is not exactly true or false. Three kinds of qualitative values of the hedge variable and their qualitative operations are presented. The truth value of a proposition with linguistic hedge has six qualitative values: T+, T, T-, F-, F+. Based on the lattice implication algebra, six linguistic truth-valued propositional logic system based on the lattice implication is introduced. Its soft-Resolution Method is discussed to deal with the linguistic hedge

Yang Xu - One of the best experts on this subject based on the ideXlab platform.

  • Resolution Method of six element linguistic truth valued intuitionistic propositional logic
    IEEE International Conference on Intelligent Systems and Knowledge Engineering, 2008
    Co-Authors: Yang Xu
    Abstract:

    Truth degree and falsity degree of intuitionistic fuzzy proposition are two truth values with linguistic hedge. In this paper, we constructed six-element intuitionistic linguistic truth-valued propositional logic(6 LTV-IP) based on the the framework of linguistic truth-valued propositional logic which can express both the comparable and incomparable truth values. With some special properties of 6 LTV-IP, we discussed the satisfiable problem of 6 LTV-IP and proposed a Resolution Method of 6 LTV-IP.

Lin Xiao - One of the best experts on this subject based on the ideXlab platform.

  • FUZZ-IEEE - A Resolution Method for linguistic truth-valued intuitionistic fuzzy first-order logic
    2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
    Co-Authors: Lin Xiao, Jia Meng, Shifei Ding, Li Zou
    Abstract:

    This research aims at finding a way to deal with the uncertain problem which has both positive evidence and negative evidence at the same time. Based on the linguistic truth-valued lattice implication algebra, we establish six-element linguistic truth-valued linguistic intuitionistic fuzzy first-order logic system. Subsequently, we present a Resolution Method of six-element linguistic truth-valued linguistic intuitionistic fuzzy first-order logic (6LTV_IFFL) and prove the soundness of it. Meanwhile, the step of Resolution Method of 6LTV_IFFL is given.

Zhang Jia-fen - One of the best experts on this subject based on the ideXlab platform.

  • α-Semantic Resolution Method Based on Lattice-valued First-order Logic LF(X)
    Computer Science, 2014
    Co-Authors: Zhang Jia-fen
    Abstract:

    Automated reasoning is one of the most important research directions in artificial intelligence.Resolutionbased automated reasoning has been extensively studied because of its easy implement on computer.Semantic Resolution Method is one of the most important modified Methods for Resolution principle in semantic Resolution Method,and it utilizes the technology that restrains the type of clauses and the order of literals participated in Resolution procedure to reduce the redundant clauses,and can improve the efficiency of reasoning.For improving the efficiency ofα-re-solution principle in lattice-valued logic based on lattice implication algebra,we applied the semantic Resolution strategy toα-Resolution principle.Firstly,this paper gave the conceptions ofα-semantic Resolution andα-semantic Resolution deduction in LF(X).Subsequently,the semantic Resolution Method on it was investigated and sound theorem and conditional complete theorem of this semantic Resolution Method were proved.At last,the effectiveness ofα-semantic Resolution Method was illustrated through an example.

J Amiaux - One of the best experts on this subject based on the ideXlab platform.

  • super Resolution Method using sparse regularization for point spread function recovery
    Astronomy and Astrophysics, 2015
    Co-Authors: F Ngole M Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-Resolution (SR) Method to recover aliased frequencies, prior to further analysis. This is particularly relevant for point-source images, which provide direct measurements of the instrument point-spread function (PSF). We introduce SPRITE, SParse Recovery of InsTrumental rEsponse, which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing Methods, especially on low SNR PSFs.

  • Super-Resolution Method using sparse regularization for point-spread function recovery
    Astronomy and Astrophysics - A&A, 2015
    Co-Authors: F. M. Ngolè Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-Resolution (SR) Method to recover aliased frequencies, prior to further analysis. This is particularly relevant for point-source images, which provide direct measurements of the instrument point-spread function (PSF). We introduce SParse Recovery of InsTrumental rEsponse (SPRITE), which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing Methods, especially on low signal-to-noise ratio PSFs.

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