In order to further improve channel estimation accuracy of LMMSE
algorithm criterion and reduce the complexity of the algorithm criterion, the channel response autocorrelation function [R.sub.hh] can be simplify processed by using the singular value decomposition (SVD) method.
Comparison of Different Interference Mitigation schemes on Signaling Transmission by Comp Technique using Lmmse
The saliency maps [[??].sub.1] and [[??].sub.2] are thus computed by applying the LMMSE
based filter q and following (2):
(2) At the first step (i = 1) of the algorithm, the LMMSE
channel estimation [22, 23] is performed with [[??].sup.LS.sub.H]:
Inspired by the effectiveness of LMMSE
mechanic used in solving state estimation problem of MJLSs with random time delays in , the problem of state estimation of MJLSs with random missing observations is formulated into LMMSE
A major drawback of LMMSE
is the complexity involved in the computation of the auto-correlation matrix.
For "SCH1", the LSE (applying (24)) and the LMMSE
estimation (applying (25)) of [[??].sup.<r>] are compared.
For example, in the case of a linear minimum mean-square-error (LMMSE
) filter, [mathematical expression not reproducible] is obtained as
In this section, we will demonstrate the performance of the proposed method and make a comparison with several stateof-the-art methods including NL-Mean , LARK , BLF , TV , K-SVD , LGM , and LMMSE
In sensing of least minimum mean square error(LMMSE
) for prediction error, the prediction parameters of the statistically optimal prediction can be expressed as
The early algorithms suppress speckles through an examination of the local statistics surrounding a given pixel using optimization criteria as the local minimum mean square error (LMMSE
), for instance, the Lee filter , the Frost filter , the Kuan filter  and their improved version [6,13].
 Saqib Saleem, Qamar-ul-Islam, "Optimization of LSE and LMMSE
Channel Estimation Algorithms based on CIR Samples and Channel Taps," IJCSI International Journal of Computer Science Issues, vol.