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Mean and entropy of b-spline PDF models: analysis and design

Zhou, J. and Yue, H. and Wang, H. (2005) Mean and entropy of b-spline PDF models: analysis and design. In: 16th IFAC World Congress, 2005, 2005-07-04 - 2005-07-08, Prague.

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Abstract

For continuous probability density functions (PDFs) approximated by the B-spline basis functions, the relationships between the B-spline weights, the entropy and the mean have been analyzed in detail. It shows the different characteristics of the entropy with and without mean constraint. A minimum entropy controller subjected to mean constraint is developed by taking the performance function as a Lyapunov function and ensuring the negativeness of its first-order derivative. Simulation examples are included to validate the analysis results and evaluate the closed-loop control performance.

Item type: Conference or Workshop Item (Paper)
ID code: 38055
Keywords: dynamic stochastic systems, probability density function (PDF), B-spline neural network, minimum entropy, mean constraint, Electrical engineering. Electronics Nuclear engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 01 Mar 2012 12:52
    Last modified: 07 Dec 2013 12:23
    URI: http://strathprints.strath.ac.uk/id/eprint/38055

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