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

Jinglin Zhou, Hong Yue, Hong Wang

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)93-98
Number of pages6
JournalIFAC Proceedings Volumes
Issue number1
Publication statusPublished - 2005
Event16th IFAC World Congress, 2005 - Prague, Czech Republic
Duration: 4 Jul 20058 Jul 2005


  • dynamic stochastic systems
  • probability density function (PDF)
  • B-spline neural network
  • minimum entropy
  • mean constraint


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