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

learn more… | top users | synonyms

3
votes
2answers
165 views

Image Processing: Flatten a 3D Ball

There are many descriptions of how to turn a 2D image into a 3D one, however I want to do the opposite, in particular to a ball. As an example, consider the following ball: If only the (relatively) ...
0
votes
1answer
39 views

Correlating accelerometer data

I am getting a signal from a device. This signal contains a non-random noise signal in it. I want to remove that noise from the signal. This noise is correlated to the motion the device is having. So ...
1
vote
1answer
37 views

Deep zeros in the spectrum of the input data?

I wanted to know the meaning of "deep zeros" in the spectrum of the input data. I came across this terminology while going through the introduction of chapter 2 (Bussgang techniques for blind ...
1
vote
1answer
123 views

Using a Wiener Filter to Estimate a Transfer Function

As a follow-on to this question about estimating a transfer function of an unknown system using a Wiener filter, How would you put a minimum MSE criteria on how well the estimated filter weights ...
0
votes
0answers
76 views

AEC Speex . How does it work?

I'm working with AEC of Speex. The algorithm is based on the MDF adaptive filter + an adaptive learning rate. I'm using it like a ANC and it works very well. Does anybody have some material, as block ...
3
votes
1answer
89 views

Correction of a signal through a transmitter

I am inquiring as to a practical way to solve a problem I have. Basically, I need to transmit a signal, $x[n]$, through a seismic transmitter. (It will go through a D/A, etc). The transmitter that ...
0
votes
2answers
260 views

scipy.signal.wiener for audio processing

Does some have an example of what a Wiener filter (that can be used directly with scipy.signal.wiener) can be useful for, in sound processing (it seems that such ...
0
votes
1answer
64 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 ...
0
votes
0answers
66 views

Need a fast algorithm of adaptive convolution

I have to apply some kind of adaptive filter to my function $f(x).$ I present each point of my signal as a Gaussian, whose bandwidth depends on its location (not the point of observation $\textbf{x}$) ...
5
votes
1answer
248 views

2D adaptive filters

Does anyone know about different adaptive filtering implementations (LMS, RLS ...) in 2D or even 3D ? I have sequences of 2D images and 3D volumes with repeating patterns but small differences. I was ...
1
vote
0answers
60 views

RLS adaptive filter

I am using an adaptive RLS adaptive filter for noise cancellation. My sampling freq. is 500 Hz, but I am interested in only frequencies of up to 60 Hz. I filter the input and the reference signal to ...
0
votes
1answer
189 views

MSE in adaptative filter

I'm trying to filter some motion noise from an ECG signal. To do that I'll try to implement an adaptive filter using the LMS algorithm. I think I have to calculate the MSE of this: ...
1
vote
0answers
336 views

adaptive filter does not converge for all inputs

I am trying to make a frequency domain adaptive filter in matlab. It uses matlab adaptfilt.fdaf to create the filter parameters like step size and initializing initial filter weight values. Then I ...
4
votes
1answer
367 views

Relative performance of RLS and LMS filters

It's known that the RLS filter converges faster than the LMS filter in general, but that if you're tracking time varying parameters the LMS algorithm can perform better. My question is under what ...
1
vote
1answer
130 views

Adjustable Notch Filter help

I'm converting the simulink diagram found in this paper to C code. I'm not familiar with matlab/simulink(too expensive) so need help interpreting the diagram. The problem I experience is that once a ...
3
votes
1answer
389 views

Difference between 'conventional' and 'adaptive' beamformers?

This might be a terminology question but I am not sure. Basically, what is the difference between conventional beamformers, and adaptive beamformers? I thought that all beamformers were inherently ...
0
votes
0answers
208 views

Maximum step size for adaptive filter convergence

I’m trying to understand the conception of function maxstep (http://www.mathworks.com/help/dsp/ref/maxstep.html) the foundation of this function is function firwiener with input parameters: length ...
14
votes
1answer
190 views

Using an error prediction filter for filtering a semi-known signal

I'm trying to wrap my head around the proper use of a Wiener or error-prediction filter for filtering data. It seems to me that it is only a whitening filter, so how is it used when the data you want ...
8
votes
1answer
1k views

What does an adaptive filter do?

I studied a bit about adaptive filter on internet and found that its a special filter which keep on updating its filter value as soon as it proceeds. It finds out the difference between input and ...
7
votes
1answer
240 views

Why does over-modelling an adaptive AR NLMS filter fix sharp spikes?

I just simulated an auto-regressive second-order model fueled by white noise and estimated the parameters with normalized least-mean-square filters of orders 1-4. As the first-order filter ...
2
votes
1answer
77 views

What are the Elements of Filters for Highly Volatility Price Series with Jumps?

What are the best filtering techniques for a highly volatility price series with jumps. What needs to be considered in designing new filters for practical finance which are adaptive and highly ...
17
votes
2answers
556 views

Should the input of a Kalman filter always be a signal and its derivative?

I always see the Kalman filter used with such input data. For example, the inputs are commonly a position and the correspondent velocity: $$ (x, \dfrac{dx}{dt}) $$ In my case, I only have 2D ...
13
votes
1answer
399 views

How do I improve LMS / NLMS filter performance?

Are there ways to increase computational performance of a normalized least squares (NLMS) filter? Multidelay block frequency-domain (MDF) filters have been proposed to do this, but they also take away ...