Open AccessSimulation and performance analysis for coefficient estimation for sinusodial signal using LMS, RLS and proposed method
Author(s) -
MVV Prasad Kantipudi,
H. N. Suresh
Publication year - 2017
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.2.8960
Subject(s) - spectral density , spectral density estimation , signal (programming language) , noise (video) , spectral power distribution , filter (signal processing) , mathematics , stochastic process , noise power , algorithm , computer science , power (physics) , statistics , artificial intelligence , mathematical analysis , physics , fourier transform , quantum mechanics , optics , image (mathematics) , computer vision , programming language
The estimated Power Spectral Density (PSD) gives the information regarding the architectural structure of random process; it can be utilized for mathematical modeling, removal of noise, prediction of the signal of the deserved processes. The objective of spectral density estimation is to approximation the spectral density of a random signal from a series of time sample of the signal. Spectral estimation and coefficient estimation is concerned with determining the distribution in frequency of the power of a random process. In this paper, a well-known adaptive filter is used to the estimation of the spectral density of the signal. It includes the LMS, RLS and improves RLS (proposed method) to analyze the coefficient of the sinusoidal signal.