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## LEAST MEAN SQUARE ALGORITHMPosted by: projectsofme Created at: Wednesday 24th of November 2010 05:13:27 AM Last Edited Or Replied at :Monday 18th of April 2011 01:46:46 AM | lms algorithm in mathematics ,
least mean squares algorithm,
linear minimum mean square error algorithms doc ,
mathematics,
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h an arbitrary value w(0) for the weight vector at n=0. The successive corrections of the weight
vector eventually leads to the minimum value of the mean squared error. for more information,please go through: http://etd.lib.fsu.edu/theses/available/etd-04092004-143712/unrestricted/Ch_6lms.pdf.................. [:=> Show Contents <=:] | |||

## LEAST MEAN SQUARE ALGORITHMPosted by: projectsofme Created at: Wednesday 24th of November 2010 05:13:27 AM Last Edited Or Replied at :Monday 18th of April 2011 01:46:46 AM | lms algorithm in mathematics ,
least mean squares algorithm,
linear minimum mean square error algorithms doc ,
mathematics,
mathmatics ,
least mean square method problems,
least mean square algorithm doc ,
least square algorithm,
seminar least mean square algorithm ,
estimate the mean vector and the covariance matrix,
least mean squares lms algorithms ,
mean square error algorithm,
| ||

ared Error (MSE) criterion. Therefore the spatial filtering problem involves estimation of
signalfrom the received signal (i.e. the array output) by minimizing the error between the reference
signal , which closely matches or has some extent of correlation with the desired signal estimate
and the beamformer output y(t) (equal to wx(t)). This is a classical Weiner filtering problem for
which the solution can be iteratively found using the LMS algorithm. LMS algorithm formulation (All signals are represented by their sample values) From the method of steepest descent, the weight vector equa.................. [:=> Show Contents <=:] |

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