Least Mean Squares (LMS) algorithm
GPTKB entity
Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
adaptive filter algorithm
|
| gptkbp:application |
noise reduction
system identification echo cancellation channel equalization |
| gptkbp:field |
gptkb:machine_learning
gptkb:signal_processing control theory |
| https://www.w3.org/2000/01/rdf-schema#label |
Least Mean Squares (LMS) algorithm
|
| gptkbp:input |
desired signal
input signal |
| gptkbp:introducedIn |
1960
|
| gptkbp:inventedBy |
gptkb:Bernard_Widrow
gptkb:Ted_Hoff |
| gptkbp:limitation |
slow convergence
sensitive to step size |
| gptkbp:output |
error signal
filter weights |
| gptkbp:parameter |
step size (μ)
|
| gptkbp:property |
robustness
low computational complexity |
| gptkbp:purpose |
minimize mean square error
|
| gptkbp:relatedTo |
gptkb:Wiener_filter
gptkb:Recursive_Least_Squares_(RLS)_algorithm |
| gptkbp:type |
stochastic gradient descent method
|
| gptkbp:updateRule |
w(n+1) = w(n) + μ e(n) x(n)
|
| gptkbp:usedIn |
gptkb:machine_learning
telecommunications audio processing image processing biomedical signal processing pattern recognition financial modeling hearing aids prediction system modeling radar signal processing system control adaptive noise cancellation echo suppression speech enhancement adaptive beamforming channel estimation adaptive equalization |
| gptkbp:variant |
gptkb:Complex_LMS
gptkb:Leaky_LMS gptkb:Normalized_LMS_(NLMS) gptkb:Sign_LMS |
| gptkbp:bfsParent |
gptkb:Normalized_LMS_(NLMS)
|
| gptkbp:bfsLayer |
7
|