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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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estimate the mean vector and the covariance matrix,
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| ||

nal and additional noise n(t). As shown above the outputs of the individual sensors are linearly
combined after being scaled using corresponding weights such that the antenna array pattern is
optimized to have maximum possible gain in the direction of the desired signal and nulls in the
direction of the interferers. The weights here will be computed using LMS algorithm based on Minimum
Squared 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 c..................[:=> 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,
| ||

ts, which forms the integral part of the adaptive beamforming system as shown in the figure below.
The output of the antenna arrayis given by, tsdenotes the desired signal arriving at angle0θθandudenotes interfering signals arriving at angle of incidences)(tiiθrespectively. a(0θ) and a(i) represents the steering vectors for the desired signal and interfering signals respectively. Therefore it is required to construct the desired signal from the received signal amid the interfering signal and additional noise n(t). As shown above the outputs of the individual sensors are linearly combi.................. [:=> Show Contents <=:] |

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