Questions tagged [lms]

Least Mean Square adaptive filter.

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53 views

How to evaluate fixed-point implementation of LMS filter is correct?

I am having an LMS block with 6 filter coefficients. The value of filter coefficients are 0.0001 0.00045 0.2535 0.546536 0.0000243 0.3423 I have tried to ...
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14 views

Expressions for steady-state LMS coefficient covariance

I've seen in the literature a few transient analyses for the LMS algorithm. These mostly focus on the mean estimation error for the LMS tap weights as well as the limiting signal estimation error ...
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48 views

Can adaptive filters filter noises that are of two different frequencies?

I am testing an adaptive filter using 5 different algorithms (LMS,NLMS,SE-LMS,SD-LMS,SS-LMS)to find which would be better fit for my application. The filter has 8 taps and my input are brain recorded ...
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12 views

Block NLMS vs Affine Projection LMS

I am studying Block Normalized LMS, and when I compare this with Affine Projection LMS (if updated every M samples) I think that they are the same. I would really appreciate if anyone can point out if ...
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2answers
62 views

How to calculate EVM in %age of an Equalized Constellation in 16QAM?

I have an equalized constellation for 16 QAM. The constellation is equalized by LMS algorithm. I want to calculate the EVM for the equalized constellation. How can I calculate this so that the EVM ...
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24 views

Capture the ambient sound

I sit in a cafe and start recording my voice, reading a poem. Then I sit at my room, at complete isolation, and I read the same exact poem once again and record it. Now, Considering I have these two ...
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1answer
93 views

Why is the error between the desired signal and estimated signal in the case of LMS filter remaining constant even after n number of iterations

I am giving white noise as input to an adaptive filter which is initialized to zero (value of filter coefficients of adaptive filter is 0). I am getting a desired response $d(n)$ by passing white ...
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50 views

Beamformer implementation methods

I'm currently reading articles about the different type of beamformers. This spatial filtering is gonna be used for acoustic purposes, to focus the beam on the person we need to hear talking in a ...
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19 views

Convergence of LMS

I'm not really sure about the following question and don't know where exactly to look it up, so I'm asking here: I have an adaptive filter and compute the coefficients iteratively using e.g. LMS or a ...
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1answer
93 views

Estimate Instantaneous Frequency Using LMS Algorithm

I hope someone can help me with the following problem: I want to estimate the frequency of a sound file that is composed of a sinusoidal with varying frequency and additive white noise: $$ x \...
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18 views

Supression of sinusoidal interference

I have a bit of project that I'm doing for SIN interference removal. Just not sure Am I doing everything correct: Fs = 1000; Ts = 1/Fs; order = 12; t = 0:Ts:1-Ts; x = sin(2*pi*4*t); noise = ...
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41 views

Length of the FIR filter in LMS algorithm

I'm working on an interference cancellation problem where interfering signals are two linear FM chirps of different slopes and the data signal is a spread spectrum signal. I wanted to know how does ...
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1answer
31 views

Unknown symbol/expression in text about adaptive filters (cst)

I am currently reading a chapter about adaptive filters from the Springer Handbook of Speech Processing. In a formulation of the variable stepsize normalized least mean squares (VSS-NLMS)-algorithm, ...
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230 views

Feedback Filtered-x LMS algorithm: question about theory

I was reading some of papers about the Active Noise Cancellation; in particular about the Filtered-x LMS algorithm, also known as FxLMS. It seems that classic FxLMS (also called Feedforward FxLMS) ...
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850 views

LMS adaptive filter noise suppression- question about my implementation

I am writing LMS filter to suppress noise in wav file (I know there are many modules to do this but I need to write LMS manually now as I will translate it into C later). According to this answer[1], ...
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1answer
130 views

Active Noise cancellation for non periodic signals

I observed that the coded algorithm for active noise cancellation is not able to cancel some of the signals like a human voice. Is there any solution for this? Can we really cancel non-periodic ...
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1answer
165 views

Can Temperature Data be Predicted Using Adaptive Filter (Such As LMS) Algorithm?

I am working on a project which requires me to implement adaptive filter as a predictor. I have just started on adaptive filter and I intend to use least mean square algorithm for weight adjustment. ...
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1answer
171 views

Implementation of Block LMS

In the implementation of block LMS, i need one clarification. In the 3rd step as shown in the figure attached, the summation over a product of input, $\mathbf{u}$ and error, $e$, associated with each ...
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1answer
88 views

Seperation of wideband and narrowband - Adaptive Filter

I have the following diagram for the adaptive seperation of a narrowband and wideband signal using LMS algorithim, The way it was explained to us was that "The narrowband signal is correlatied over ...
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33 views

NLMS Echo Cancellation: How do we estimate when the time-step at which the Far-End Echo will be generated?

I'm new to this domain. From my understanding, we do the following in our algo: ...
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1answer
418 views

estimate the impulse response after equalization

I want to estimate the impulse response of the channel at the receiver. Assuming some arbitrary impulse response: h=[1 0.2 -0.4 0.0 0.6]. Once the equalizer is ...
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1answer
464 views

Recursive Least Square Adaptive Linear Equalizer

For the adaptive filter to work properly, a desired signal d(n) needs to be provided. The output from the equalizer y(n) is subtracted from d(n) to produce an error signal, which is used to adjust the ...
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1answer
59 views

Fair performance comparison betweem LMS & NLMS

How can I choose the step size $\mu$, when I'm comparing different algorithms such as LMS, NLMS and transform domain adaptive filters, regarding their convergence speed, to get a fair comparison ...
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2answers
1k views

what is an alpha filter?

Currently, I'm working on adaptive beamforming using LMS approach, so they change the value of the step factor adaptively in which one of the steps is to pass the weight vector through an alpha filter....
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122 views

Generalized Sidelobe Cancelling performance

I'm tinkering with different adaptive beam-forming algorithms for a research project in which I want to use a Uniform Rectangular microphones Array (URA) to isolate speech in a room. I am determining ...
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169 views

Equalizer design for spectral gain flatness

I'm trying to design an equalizer for spectral flatness over a 100MHz signal for an LTE channel emulator. A channel emulator simply multiples channel coefficients with an external signal from a signal ...
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1answer
112 views

Block LMS with overlapping blocks

In the Block LMS algorithm, the input is partitioned into nonoverlapping blocks of size $L$ and the filter coefficients are updated once every $L$ samples. Would convergence improve if we used more ...
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1answer
414 views

Why does block LMS have the same performance as LMS?

The block LMS and conventional LMS have the same convergence rate and the same misadjustment. I am having trouble wrapping my head around this. The block LMS uses a more accurate estimate of the ...
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1answer
213 views

Doubts on LMS derivation

I have been trying to follow the Least Mean Square(LMS) algorithm derivation given by Wikipedia here and have the following questions. Here I expected $y(n)$ is to be computed by convolving $x(n)$ ...
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488 views

Equalizer coefficients and channel coefficients

Blind channel equalization methods equalize the channel without using the source data and without knowing the impulse response of the channel. Consider the channel to be a single input single output ...
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1answer
2k views

What do the filter coefficients in digital filter represent?

Could you help me? How can I understand the function of the filter coefficients practically? In the simple case, it is the impulse response of the LTI system. but how do they work?
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58 views

Error plot between known and estimated data

The channel is an FIR model with input $u$. The input takes in values which are symbols from some constellation. Using an equalizer such as the Least Mean Squares (LMS), I estimate the input to the ...
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75 views

Normalized LMS with a posteriori Error and Woodburry's Matrix Inversion

I was going through this paper and the author mentioned that we can prove the following using the Matrix Inversion Lemma (AKA Woodburry's Matrix Inversion Identity): Using matrix inversion lemma we ...
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1answer
157 views

Recursive DCT implementation

I am trying to understand the recursive implementation of the DCT on the input signal (used for LMS filtering) according to the pictures below. The pictures and formulas are taken from the paper: "...
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1answer
246 views

Model Validation After Estimation for System Identification Task (Assistance with MATLAB Code)

QUESTION: I want to determine how well the estimated model fits to the future new data. How do I validate the estimated model...what is the procedure? After system identification, how to do model ...
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1answer
584 views

Unable to understand the derivation of the update equation for LMS

I am trying to follow the derivation of the Least Mean Square https://en.wikipedia.org/wiki/Least_mean_squares_filter#Proof but I cannot get the update rule. I am stuck in the following steps and ...
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2answers
402 views

Explain the Adaptive Part of Adaptive Algorithms - Kalman Filter and Least Mean Square / Constant Modulus

General questions: Is the Kalman filter (they have used Unscented Kalman Filter) adaptive or not? Is the Unscented Kalman Filter used in the paper an adaptive algorithm? Adaptive algorithms such as ...
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1answer
1k views

Maximum Likelihood Estimator (MLE), MMSE and LS - Are All of Them Regressor, Estimator and Predictor?

Can all three criteria ML, MMSE, and LS be called regressor, estimator, and predictor ? If not, an intuitive explanation of why they can't be, would be good.
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1answer
152 views

Two type of calculating R in steepest-descent modeling algorithm

I have wrote this algorithm for steepest descent: ...
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1answer
1k views

LMS algorithm for modeling step-size ambiguity!

Behrouz Farhang-Boroujeny in his adoptive filters, 2nd ed., p. 155 ,told: It is sufficient for stability: 1/(3*tr(R)). But his book have attached mfile for ...
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2answers
74 views

Stochastic approximation algorithm

The goal is to find the FIR filter coefficients $\mathbf{h} = [5;3]$ with the help of the adaptive FIR filter $\mathbf{w}$ of order $p = 2$. I have implemented the Stochastic approximation algorithm ...
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1answer
349 views

LMS and delta impulse response- Equalization concepts

I have been reading about equalization and channel estimation in order to apply to my application of estimating trajectory path for a two-wheeled robot. The application is quite similar to ...
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1answer
213 views

Why is my NLMS filter off by +/- 2?

I haven't done any signal processing in a while, but I'm completely stymied by the instability and bias in my implementation of a normalized least mean squares filter. I checked the usual things: Am ...
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2answers
71 views

Upsampled input to an Adaptive filter?

I will try to explain the issue I am having as clearly as possible without going into my coding or maths. I have my own and a MATLAB Central implementation pf standard LMS in MATLAB. Fixed step size. ...
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105 views

Gradient descent applying chain rule in state space setup

Trying to perform system identification in the following state-space model $$ \begin{bmatrix} x_{1}(n)\\ x_{2}(n) \\ x_{3}(n)\end{bmatrix}=\begin{bmatrix} a_{11} && a_{12} && a_{13} \\ ...
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1answer
442 views

Variable Step Size LMS vs Leaky LMS Adaptive Filter Algorithm

What is the advantage of Variable step size LMS over Leaky-LMS adaptive filter algorithm? Which one has a better performance?
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2answers
997 views

LMS Algorithm: How to Define the Desired Signal

I am working on LMS algorithm,i am not getting exactly how we get desired response of the filter that is compared with the estimated output