Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 21, Pages: 1-5
D. Rajitha1 *, S. Koteswarao Rao2 , P. Suneetha1 * and R. Aamani1
1 Department of ECE, Vignan’s Institute of Information Technology, [email protected]
2 Department of ECE, KL University, [email protected]
*Author For Correspondence
Department of ECE
Objective: Stochastic process have been performed useful in applications of signal and image processing in varied applications .Kalman filters are examples of such processing in state space time domain AR signals, AR process can be used as models of natural phenomena. Methods/Analysis: This paper explores the applications of Kalman filter AR signal processing using LMS in second algorithm, convergence speed is studied. RLS algorithm ensures fast convergences. Findings: Predictor - connector algorithm is used for mathematical modeling estimation of constant or random constant having process clatter in AR process has been done by discrete Kalman filter. It is formed that where covariance and dimensions clatter are invariable, the evaluation ever covariance and Kalman gain stabilized quickly. These limitations can be pre work out by running to filter off size. Novelty/Improvement: Estimation of true state by implement of discrete Kalman filter has shown that results are satisfied. Further extension can be done to estimate other stochastic parameters.
Keywords: AR Signals, Discrete Kalman Filter, RLS Algorithm, Stochastic Process, Time Domain
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