Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:advantage |
slow convergence
sensitive to step size computationally simple |
| gptkbp:application |
system modeling
speech enhancement acoustic echo cancellation adaptive equalization |
| gptkbp:category |
linear adaptive filter
|
| gptkbp:field |
gptkb:machine_learning
gptkb:signal_processing adaptive filtering |
| gptkbp:form |
stochastic gradient descent
|
| https://www.w3.org/2000/01/rdf-schema#label |
Least Mean Squares (LMS)
|
| gptkbp:input |
desired signal
input signal |
| gptkbp:introduced |
gptkb:Bernard_Widrow
gptkb:Ted_Hoff |
| gptkbp:introducedIn |
1960
|
| gptkbp:objective |
mean squared error
|
| gptkbp:output |
error signal
filter weights |
| gptkbp:parameter |
step size (μ)
|
| gptkbp:purpose |
minimize mean square error
|
| gptkbp:relatedTo |
gptkb:Wiener_filter
gptkb:Recursive_Least_Squares_(RLS) gradient descent |
| gptkbp:updateRule |
w(n+1) = w(n) + μ e(n) x(n)
|
| gptkbp:usedIn |
gptkb:radar
biomedical engineering communications control systems telecommunications audio processing image processing financial modeling system identification adaptive control echo cancellation seismic data processing adaptive noise cancellation channel equalization antenna array processing |
| gptkbp:variant |
gptkb:Block_LMS
gptkb:Complex_LMS gptkb:Normalized_LMS_(NLMS) gptkb:Sign_LMS gptkb:Frequency-domain_LMS |
| gptkbp:bfsParent |
gptkb:Adaptive_Signal_Processing
|
| gptkbp:bfsLayer |
6
|