about wiener filter theory
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最近在学习weiner filter. 发现就是一个linear filter. which includes the several elements. this filter is used in stationary environment.
1, the wiener filter problem statement
it is to minimizes the mean-squared error(MSE) due to estimation
2.solution to wiener filter problem
is to find the optimum weights for the filer to make the MSE minimum. it require the Wiener-Hopf equation and Hessian matrix.
The problem is like to solve the wiener-hopf equation and it requires inverse of a square matrix.
3.to solve the inverse of a square matrix, it is difficult so we have another method to do. it is the least mean-square algorithm which rely on the assumption "an optimal and unique solution exists"
4. also the convergence of the LMS algorithm is also analysed.
The first order and the second order. however i did not know what is the different between them. the first one is base on the equation of the LMS algorithm and the second is base on the mean-squared error which is second order statistics.
this is summary
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