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Project on

ALE USING FLMS ALGORITHM Prepared by :

Mr Prabhash K Singh (Communication System,12531012)

Mr. Sreekanth CB (Communication System,12531014)

7/27/2019 r.pptx


BLMS(Block Least Mean Square)

• Incoming data sequence is sectioned into

blocks using serial to parallel converter.

• Block of input data are applied to FIR filter one

block at a time.

• Adaptation of filter proceeds on a block by

block basis rather than sample by sample

basis as in conventional LMS algorithm.

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FLMS(Fast Least Mean Square)

• BLMS requires both linear convolution and linearcorrelation in its implementation.

• FFT provides powerful tool for faster convolutionand faster correlation.

• A frequency domain implementation of BLMS willbe more efficient.

• FLMS is the frequency domain implementation of

BLMS• Computationally more efficient than Block-

LMS(more than 15 times).

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FLMS Algorithm

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Algorithm continued…..

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ALE Using FLMS Algorithm

• Generate a signal of the forms(n) = A sin(2πf1n/Fs) + B sin(2πf2n/Fs)Fs = sampling Frequency

• A noise w(n) is added to the signal to produce the noisy signald(n) = s(n) + w(n)

• The noise is a white uniformly distributed sequence with zeromean. The SNR of this signal should about -7 dB. The desired signal( or primary signal) is d(n). The reference signal is d(n−1) and isapplied to the input of an N-tap FIR filter that produces the outputy(n), which should be the estimate of the signal. Use the LMSalgorithm for adaptation. Choose N and the step size appropriately

for good results.

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Part one:

• Experiment with different block lengths of

L=100, 200, 400, 800, and 1000. Discuss the

effect of the block length on convergence, if

any. How does the computational change with

the block length? Using SNR=10

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Fig 1: Block length=100

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• Effect of Block length on convergence:

when block length increases

1. convergence didn’t happen. To maintainconvergence we have to decrease the step

size.

2. computational complexity decreases for

same number of iterations

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• Optimal choice is block length = filter length,its computationally more efficient.

• When

block length < filter length-advantage of reduced processing delay

-still more efficient than conventional LMS.

block length > filter lengththere is redundant operations in adaptive

process

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Part 2: FLMS v/s LMS

• FLMS is computationally more efficient.

• FLMS converges at a faster rate than LMS.

•

Convergence rate of FLMS can be furtherimproved by assigning different step size for

each weight.

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Part 3:

• In the FLMS, contiguous blocks of data are

used. One variantion is to use partially

overlapping blocks in order to gain convergent

speed. Use overlaps of L/4, L/2 and 3L/4 andrepeat your experiments Discuss the

performance of the algorithm.

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• As overlapping between block elements

increases their convergence is also faster.

• But need more computation is involved.

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!!! THANK YOU !!!

r.pptx

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