Introduction To Stochastic Control Theory

In This Book, We Study Theoretical And Practical Aspects Of Computing Methods For Mathematical Modelling Of Nonlinear Systems. A Number Of Computing Techniques Are Considered, Such As Methods Of Operator Approximation With Any Given Accuracy; Operator Interpolation Techniques Including A Non-lagrange Interpolation; Methods Of System Representation Subject To Constraints Associated With Concepts Of Causality, Memory And Stationarity; Methods Of System Representation With An Accuracy That Is The Best Within A Given Class Of Models; Methods Of Covariance Matrix Estimation; Methods For Low-rank Matrix Approximations; Hybrid Methods Based On A Combination Of Iterative Procedures And Best Operator Approximation; And Methods For Information Compression And Filtering Under Condition That A Filter Model Should Satisfy Restrictions Associated With Causality And Different Types Of Memory. As A Result, The Book Represents A Blend Of New Methods In General Computational Analysis, And Specific, But Also Generic, Techniques For Study Of Systems Theory Ant Its Particular Branches, Such As Optimal Filtering And Information Compression. - Best Operator Approximation, - Non-lagrange Interpolation, - Generic Karhunen-loeve Transform - Generalised Low-rank Matrix Approximation - Optimal Data Compression - Optimal Nonlinear Filtering