New results in Sridhar filtering theory: The discrete case

Autor:	A. S. Abutaleb, M. Papaiouannou
Rok vydání:	1990
Předmět:	Control and Optimization Applied Mathematics Filter (signal processing) Management Science and Operations Research Filter bank Adaptive filter Filter design Autoregressive model Control theory Kernel adaptive filter Filtering problem Autoregressive–moving-average model Algorithm Mathematics
Zdroj:	Journal of Optimization Theory and Applications. 64:5-14
ISSN:	1573-2878 0022-3239
Popis:	A nonlinear time-varying adaptive filter is introduced, and its derivation using optimal control concepts is given in detail. The filter, which is called the discrete Pontryagin filter, is basically an extension to Sridhar filtering theory. The proposed approach can easily replace the conventional methods of autoregressive (AR) and autoregressive moving average (ARMA) models in their many applications. Instead of using a large number of time-invariant parameters to describe the signal or the time series, a single time-varying function is enough. This function is estimated using optimization techniques. Many features are gained using this approach, such as simpler and compact filter equations and better overall accuracy. The statistical properties of the filter are given, and it is shown that the signal estimate will converge in thepth mean to the true value.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8789b77e3436d17f41beda1189849a6a https://doi.org/10.1007/bf00940018 Zobrazit plný text záznamu Full text from SpringerLink