Questions tagged [adaptive-filters]

An adaptive filter is a filter that self-adjusts its transfer function according to an optimization algorithm driven by an error signal.

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Acoustic Echo Cancellation

I have the following diagram for acoustic echo cancellation I'm having a hard time figuring out what's present on the top and bottom lines in terms of reflected echos, original signal etc. Here's ...
1 vote
1 answer
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Echo Cancellation over Voice Telephone Network

I'm a bit confused about the way echo canellation over a voice telephone network works like in the following figure My issue is with the fact that the point of the adaptive filter and LMS algorithim ...
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1 answer
350 views

System Identification using LMS Adaptive Filter

I just have a question about using an least-mean-squares algorithim adaptive filter for system identification. Consider the following I am told that as the error converges to a small value, the ...
3 votes
2 answers
559 views

Bandpass filter that automatically adapts its bandwidth when a transient is detected (to avoid to smoothen the transient)

Let's say we want to isolate a band 1000 hz +/- 50 hz. Obviously, limiting the bandwidth by applying a passband filter will always destroy a bit the sharp transients (a Dirac or a rectangular ...
1 vote
3 answers
86 views

Usefulness of Practical filter ouptput

If a practical filter can't remove all unwanted frequency components like ideal filter, does that mean unwanted frequency component are still present after filtering? how can we use such distorted ...
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How general are adaptive-filtering techniques? [closed]

How often do problems arise that let you use adaptive filters? Unless I am understanding something incorrectly it seems the requirement that the input signal be stationary(or even WSS) is too strong ...
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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: ...
2 votes
2 answers
185 views

Finding the auto-correlation sequence $r_{xx}[k]$ for an AR(2) process

Consider the following recursive difference equation of a LTI system, where $v[n]$ is a white noise, zero-mean process with $\sigma_v^2 = 1$. $ x[n] = v[n] + 0.75x[n-1]-0.25x[n-2] $ I want to ...
1 vote
1 answer
679 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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186 views

Modeling channel response as complex vs splitting I and Q

If I have a communications channel where a digital QAM signal is transmitted, I can either model the channel's impulse response as a complex $h(t)$, or as 2 separate impulse responses $p(t)$ and $q(t)$...
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184 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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1 answer
1k 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 ...
3 votes
1 answer
599 views

Hardware requirements for ambient active noise cancallation system using adaptive LMS

Background I'm working on a hobby project to reduce ambient low-frequency noise generated from HVAC equipment within a small area of a room. The noise is predictable and concentrated between 55Hz and ...
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How do state of the art echo cancellation algorithms deal with variable propagation times of sound due to multiple speakers or reverberation?

I understand how echo cancellation works with a single speaker and no reverberation (using adaptive filtering and freezing the coefficients during double-talk). However, in cases with more than one ...
2 votes
1 answer
159 views

Adaptive Filter Gradient Descent

The quadratic performance surface of an adaptive filter is a paraboloid. Its minimum can be found wherever the gradient is zero. However, since there are two types of paraboloids (elliptical and ...
3 votes
2 answers
225 views

Estimation of Input Signal to Obtain the Desired Output Signal for an Unknown Filter

Suppose $h(n)$ is a finite impulse response which is unknown. We can feed any input signal $x(n)$ into the system and observe the corresponding output signal $y(n)$. From this, is it possible to ...
1 vote
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Adaptive algorithm for active noise control

I'm looking at building a cost-effective active noise control system. Basically, the system comprises two microphones - one reference and one error. A DSP unit samples and phase flips the reference ...
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1 answer
183 views

Adaptive filter to scale and phase shift two sensors output

One way of separating downgoing and upgoing wavefields in offshore seimic processing is to add signals from hydrophone and vertical component of the geophone (they are co-located). Hydrophone only ...
4 votes
1 answer
2k views

Are there any open source libraries for Adaptive noise cancellation?

I'm creating a chat application where people can input text via speech and I need to implement noise cancellation using Adaptive noise cancellation technique. I'm using dual microphones for this ...
3 votes
1 answer
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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 $x(n)$ ...
2 votes
1 answer
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Can I have some feedback on this research paper?

I have submitted this paper "Effect of Transducer Positioning in Active Noise Control" to arXiv. I would like to get some feedback on the methodology of the same. Inputs of any sort are welcome. Can ...
-1 votes
1 answer
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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?
1 vote
1 answer
402 views

RLS Algorithm (Memoryless)

I have been studying the adaptive filters lately and now when I am at RLS (Recursive Least Squar) Algorithm I came across the term used in the weighting function of the RLS called forgetting factor ($\...
4 votes
1 answer
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MATLAB : Proper estimation of weights and how to calculate MSE for QPSK signal for Constant Modulus Algorithm

I had asked conceptual Question about Constant Modulus Algorithm. I am implementing the simple steps of the algorithm, as I do not have the cma() built in module. ...
1 vote
1 answer
255 views

Filter bank for complex spectrum

I'm using a complex-valued baseband signal as my input for subband adaptive filtering. Therefore i have a complex input spectrum. My problem is now, how to split my complex spectrum into $N$ equally ...
2 votes
1 answer
431 views

MATLAB Adaptive Filters

In the audio domain, I am currently attempting to use MATLAB to distil: $\textrm{signal}$ from $\textrm{noise + signal}$ $\textrm{noise}$ from $\textrm{noise + signal}$ using two adaptive filters $\...
2 votes
1 answer
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Removing low frequencies from a signal

I am trying to remove low frequencies from a signal and intuitively I chose the high-pass filter, more specifically - a Butterworth filter, Order 4 (because I am not sure how to choose properly the ...
1 vote
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669 views

Maximum step size for adaptive filter convergence

I’m trying to understand the conception of function maxstep The foundation of this function is function firwiener with input parameters: length of adaptive ...
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Signal chain for voice calls including adaptive noise cancellation, adaptive echo cancellation, and automatic gain control and their algorithms

I am trying to understand the entire signal chain and all the algorithms associated with adaptive filtering as mentioned in the case above. From my understanding: Adaptive noise filtering (ANF)- can ...
1 vote
1 answer
218 views

Performance of adaptive filters

Can somebody please provide an intuitive answer or reference for the following questions? Q1: Dependence of estimation performance on number of data points -- I could not find any information whether ...
1 vote
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875 views

Noise cancellation using RLS filter

I am trying to create an adaptive noise canceller using the RLS algorithm. The dsp toolbox from matlab offers the RLS adaptive filter already implemented, so this saved me some trouble. My goal is to ...
5 votes
1 answer
872 views

Frequency tracking with huge noise

I'm working on a frequency tracking problem with noise, where the amplitude of the noise is orders of magnitude higher than the amplitude of my signal (~1000x). Some details: The signal is roughly ...
-1 votes
2 answers
782 views

Levinson Method

i have just one question about Levinson, my question is: can we apply this method to determine the coefficients for FIR filter? if yes, please help me ! this is an example: ...
1 vote
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498 views

SNR for channel after equalization

Suppose I have a channel described by $h[n]$ or $H(z)$ over which I send a simple PAM2 signal. After the channel AWGN is added. What is the best possible SNR with equalization? As suggested in the ...
1 vote
1 answer
477 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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2 answers
118 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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1 answer
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Using recursive least square filter

I am fairly new to the signal processing world and that being said I have little to no experience. The problem that I am having is that I am not quite sure how to use ...
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Adaptive equalizer for BPSK signals with frequency offset

I'm trying to equalize a BPSK signal which has a residual frequency offset on it. This frequency offset is dealt with at a later stage in the DSP chain, along with phase estimation. I have ...
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2 answers
82 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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546 views

Wiener filter yielding negative MSE (and MMSE)

I implement a Wiener filter using the following code ...
1 vote
2 answers
232 views

Can LMS filter converge to sparse solution?

Consider received signal $r=h*s$, where $h$ is the channel and $s$ is transmitted signal. Now from $r$ ( $s$ is known) can we predict $h$ using LMS algorithm under all conditions? I was under ...
8 votes
1 answer
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Adaptive filtering: Optimum filter length and delay

I'm trying to find the optimum filter length for an Adaptive Filtering, using RLS Algorithm. I'm using this design: So the "error" signal is the signal without noise (and that's the signal that I ...
2 votes
1 answer
1k views

Adjustment of window length with sliding/moving RMS method for frequency drifts

I'm using a sliding RMS mechanism to compute RMS of a signal, i.e. with a window size of N, I add the squared value of the new sample $x[n]$ to the running total while deducting the squared value of ...
4 votes
1 answer
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How to include phase in a sinusoidal Kalman Filter

I start with the equation for sinusoidal motion with an offset and differentiate to get the 2nd order ODE describing the motion of the object. \begin{align} x &= A\sin(\omega t + \phi) + O\\ \dot{...
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Channel Estimation / Equalization - Estimate Channel Inverse Using White Noise Statistics Only

Given the system defined in the following figure: We have a system $ G \left( f \right) $ which is unknown yet can be defined by $ {N}_{p} $ poles and $ {N}_{z} $ zeros. The signal $ x \left( t \...
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Wiener-Hopf equation [closed]

The Wiener-Hopf is given by $$\mathbf W_\text{opt} = \mathbf R^{-1} \mathbf P$$ What if the matrix $\mathbf R$ is almost singular? When $\mathbf R$ is singular, the inverse of $\mathbf R$ does not ...
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Transient and steady-state analysis for adaptive filter

I have got review for my work saying, that my work (adaptive filter variant) should be analyzed in transient and steady-state before claiming it improves performance. I have done common (in my ...
2 votes
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Speex echo cancellation takes a long time (~20s) to converge

I have been experimenting with Speex's echo canceller during the past few days. I got the echo canceller to work, however, it takes a long time until it actually begins filtering out the echo. It ...
0 votes
1 answer
627 views

First order Wiener–Hopf filter design

Consider a random process with auto-correlation function: $$r_{\rm dd} [k] = \beta^{\lvert k \rvert}\quad\text{where}\quad 0 < \beta < 1. $$ Suppose also that the observation is: $$ x[n] =...
2 votes
1 answer
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How do I quantify the amount of information being lost by filtering a digital signal?

Let's say I'm doing feature extraction from some sensor reading using a DTW algorithm. I want to extract and catalogue a set of features. Before I send my signal over to the DTW extractor, I have ...