ON MINIMUM-MEAN-SQUARED ERROR NONLINEAR FILTERING.
PRINCETON UNIV N J DEPT OF ELECTRICAL ENGINEERING
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The study is concerned with the minimum-mean-squared error MMSE nonlinear filtering of signals in additive noise. Methods of analysis, representation, and classification of non-linear systems are treated. Integral representations and their applicability to random inputs and MMSE filtering are emphasized. The general MMSE nonlinear filtering problem is discussed briefly the restriction of the filter to general classes of systems or input processes is considered. Usually the general solutions to the problem are difficult and in many cases are impractical therefore restriction to special classes of systems and special classes of input processes is investigated. Author
- Statistics and Probability