The Experts below are selected from a list of 66 Experts worldwide ranked by ideXlab platform

Yongchuan Tang - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy modeling incorporated with fuzzy d s theory and fuzzy naive bayes
    Australasian Joint Conference on Artificial Intelligence, 2004
    Co-Authors: Jiacheng Zheng, Yongchuan Tang
    Abstract:

    In fuzzy model, the consequent of fuzzy rule is often determined with degrees of belief or credibility because of vague information originating from evidence not strong enough and “lack of specificity” In this paper, we present a fuzzy model incorporated with fuzzy Dempster-Shafer Theory The consequent of fuzzy rule is not fuzzy propositions, but fuzzy Dempster-Shafer granules The salient aspect of the work is that a very simplified Analytic Output of fuzzy model which is a special case of Sugeno-type fuzzy model is achieved when all fuzzy sets in fuzzy partition of the Output space have the same power (the area under the membership function), and the determination of basic probability assignments associated with fuzzy Dempster-Shafer belief structure using fuzzy Naive Bayes The construction method of fuzzy Naive Bayes and an learning strategy generating fuzzy rules from training data are proposed in this paper A well-known example about time series prediction is tested, the prediction results show that our fuzzy modeling is very efficient and has strong expressive power to represent the complex system with uncertain situation.

  • Australian Conference on Artificial Intelligence - Fuzzy modeling incorporated with fuzzy d-s theory and fuzzy naive bayes
    Lecture Notes in Computer Science, 2004
    Co-Authors: Jiacheng Zheng, Yongchuan Tang
    Abstract:

    In fuzzy model, the consequent of fuzzy rule is often determined with degrees of belief or credibility because of vague information originating from evidence not strong enough and “lack of specificity” In this paper, we present a fuzzy model incorporated with fuzzy Dempster-Shafer Theory The consequent of fuzzy rule is not fuzzy propositions, but fuzzy Dempster-Shafer granules The salient aspect of the work is that a very simplified Analytic Output of fuzzy model which is a special case of Sugeno-type fuzzy model is achieved when all fuzzy sets in fuzzy partition of the Output space have the same power (the area under the membership function), and the determination of basic probability assignments associated with fuzzy Dempster-Shafer belief structure using fuzzy Naive Bayes The construction method of fuzzy Naive Bayes and an learning strategy generating fuzzy rules from training data are proposed in this paper A well-known example about time series prediction is tested, the prediction results show that our fuzzy modeling is very efficient and has strong expressive power to represent the complex system with uncertain situation.

Jiacheng Zheng - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy modeling incorporated with fuzzy d s theory and fuzzy naive bayes
    Australasian Joint Conference on Artificial Intelligence, 2004
    Co-Authors: Jiacheng Zheng, Yongchuan Tang
    Abstract:

    In fuzzy model, the consequent of fuzzy rule is often determined with degrees of belief or credibility because of vague information originating from evidence not strong enough and “lack of specificity” In this paper, we present a fuzzy model incorporated with fuzzy Dempster-Shafer Theory The consequent of fuzzy rule is not fuzzy propositions, but fuzzy Dempster-Shafer granules The salient aspect of the work is that a very simplified Analytic Output of fuzzy model which is a special case of Sugeno-type fuzzy model is achieved when all fuzzy sets in fuzzy partition of the Output space have the same power (the area under the membership function), and the determination of basic probability assignments associated with fuzzy Dempster-Shafer belief structure using fuzzy Naive Bayes The construction method of fuzzy Naive Bayes and an learning strategy generating fuzzy rules from training data are proposed in this paper A well-known example about time series prediction is tested, the prediction results show that our fuzzy modeling is very efficient and has strong expressive power to represent the complex system with uncertain situation.

  • Australian Conference on Artificial Intelligence - Fuzzy modeling incorporated with fuzzy d-s theory and fuzzy naive bayes
    Lecture Notes in Computer Science, 2004
    Co-Authors: Jiacheng Zheng, Yongchuan Tang
    Abstract:

    In fuzzy model, the consequent of fuzzy rule is often determined with degrees of belief or credibility because of vague information originating from evidence not strong enough and “lack of specificity” In this paper, we present a fuzzy model incorporated with fuzzy Dempster-Shafer Theory The consequent of fuzzy rule is not fuzzy propositions, but fuzzy Dempster-Shafer granules The salient aspect of the work is that a very simplified Analytic Output of fuzzy model which is a special case of Sugeno-type fuzzy model is achieved when all fuzzy sets in fuzzy partition of the Output space have the same power (the area under the membership function), and the determination of basic probability assignments associated with fuzzy Dempster-Shafer belief structure using fuzzy Naive Bayes The construction method of fuzzy Naive Bayes and an learning strategy generating fuzzy rules from training data are proposed in this paper A well-known example about time series prediction is tested, the prediction results show that our fuzzy modeling is very efficient and has strong expressive power to represent the complex system with uncertain situation.

Nossek, Josef A. - One of the best experts on this subject based on the ideXlab platform.

  • An Analytic signal model for flip-flop based phase-frequency detectors
    'Institution of Engineering and Technology (IET)', 2017
    Co-Authors: Winterstein Andreas, Nossek, Josef A.
    Abstract:

    Flip-flop based phase-frequency detectors are widely used in phase-locked loop circuits. These devices are usually assumed to behave linearly although they consist of non-linear parts. In this work, we analyze a flip-flop based phase-frequency detector circuit. Analytic Output signal models are derived for arbitrary input signal frequencies and phases. Exact and approximate closed form solutions are found for different frequency ratios. The model is validated by numerical time domain simulations

Josef A. Nossek - One of the best experts on this subject based on the ideXlab platform.

  • Analytic signal model for flip-flop based phase-frequency detectors
    Electronics Letters, 2018
    Co-Authors: Andreas Winterstein, Josef A. Nossek
    Abstract:

    Flip-flop based phase-frequency detectors are widely used in phase-locked loop circuits. These devices are usually assumed to behave linearly although they consist of non-linear parts. In this work, a flip-flop based phase-frequency detector circuit is analysed. Analytic Output signal models are derived for arbitrary input signal frequencies and phases. Exact and approximate closed-form solutions are found for different frequency ratios. The model is validated by numerical time-domain simulations.

Chimin Tsai - One of the best experts on this subject based on the ideXlab platform.

  • Design of Quadrature Mirror Filter Banks Using Complex Half-Band Filters
    2011 International Conference on Multimedia and Signal Processing, 2011
    Co-Authors: Chimin Tsai
    Abstract:

    This paper presents the theory and design examples for a new class of quadrature mirror filter banks. Two-channel filter banks are considered as a single filter with complex coefficients. The alias-free condition for the conventional two-channel quadrature mirror filter bank is analyzed and expressed in complex arithmetic. For any real coefficient digital filter, a phase shift in frequency domain produces a complex coefficient digital filter. In particular, a 90 degree phase shift for half-band digital filters results in a complex coefficient version. Such filters generate Analytic Output signals, and may be decomposed into the sum of an identity operation and a Hilbert transformer. Quadrature mirror filter banks based on complex half-band filters are investigated using the above complex arithmetic technique. Design examples and their associated polyphase realizations are included for the cases of linear phase FIR and elliptic IIR filter banks.