• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2016, Volume: 9, Issue: 31, Pages: 1-4

Original Article

Noise Cancellation in Monte Carlo Simulation


For processing signals and in control application filters are essential, linear optimums discrete time filters such as wiener filter and Kalman filter are on orthogonal principle. For non stationary cases of having a presence of noise, adaptive wiener filter has to be applied using Monte Carlo Simulation 250 samples were used for 50 runs. Coefficients of linear filter are used to estimate the additive white noise. Error is calculated and RMS value of each error is added to the sample for desired signal. FIR wiener filters of order 6, 12, 24 were chosen for adaptive operators .Simulation results were quite encourage in the sense that noise was suppressed to maximum extends. Adaptive methods noisy higher number of samples and more than 100 runs are linear to yield better results. 
Keywords: Noise Cancellation, Monte Carlo Simulation, Wiener Filter, Optimal Filter, Wiener-Hopf Equations, Wide-Sense Stationary Random Processes, Discrete Wiener Filter, Discrete Kalman Filter


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