## Forums Search for: Wiener Filter

## Channel Correlatoin Function & Noise Varaince

In OFDM Channel Estimation, we firstly get a raw channel estimate from the pilots and then perform interpolation for the remaining subcarriers. ...

In OFDM Channel Estimation, we firstly get a raw channel estimate from the pilots and then perform interpolation for the remaining subcarriers. A popular cited method is the 1D Wiener method which basically looks for a set of MMSE weights. The formula requires the correlation of the channel in the each subcarrier and the noise variance. Most text will assume that this is known. Being new to th...

## LPC Question

inIn LPC we estimate a 10th order all pole model of quasi-stationary speech. The predicted speech is...

In LPC we estimate a 10th order all pole model of quasi-stationary speech. The predicted speech is then y(k)=-a1y(k-1)-a2y(k-2)....-a10y(k-n) Is the 'gain' estimated at all ie the variance of the driving noise of the AR model? Also is this really a predictor? It is not a Wiener predictor in the sense there is no additive white noise and it is only predicting one step. Looks more like ...

## deconvolution techniques

inIn dielectric samples, a pulse of electric field makes charge plans moving, creating an acoustic wave transformed in tension, using a piezo...

In dielectric samples, a pulse of electric field makes charge plans moving, creating an acoustic wave transformed in tension, using a piezo transducer. I have a signal to deconvolute to recover the space charge profile. I know the impulse response. Today, the only thing working is to divide and filter the low frequencies with a gaussian. I tried Wiener, richardson-lucy, doesn't work. I'm looki...

## Wiener filters for transient deconvolution

inHi folks. I'm sitting here with some data recorded by a sonar. The sonar is directed vertically, insonifying a layered sea floor. My job is...

Hi folks. I'm sitting here with some data recorded by a sonar. The sonar is directed vertically, insonifying a layered sea floor. My job is to try to estimate the reflection series for this sea floor. I have both a nominal source wavelet (i.e. the analytical expression for the emitted pulse) and a reference recording, where the sonar was directed towards a reciever that was suspended ...

## Questions about QR-RLS algorithm and antenna beamforming

inHi, I want to simulate an adaptive beamforming algorithm (using QR-RLS). From what I learned, I have the following thoughts and...

Hi, I want to simulate an adaptive beamforming algorithm (using QR-RLS). From what I learned, I have the following thoughts and questions. Because I am not sure whether they are right or not (and the question is still unsolved), I want to get your answer to these. From ?Adaptive Filter Theory? of Simon Haykin, 4th edition, Page 115, "The essence of a Wiener filter is that it minimizes the me...

## estimating maximum performance of a filter, adaptive filtering, Wiener filtering

Hi everyone, currently I try to understand adaptive filtering a little deeper, and on this way stumbled over a problem. Surely someone could...

Hi everyone, currently I try to understand adaptive filtering a little deeper, and on this way stumbled over a problem. Surely someone could comment my thoughts, wheather I'm right or wrong...and provide some advice which way to think further? Imagine some filtering problem where you have a distorted signal d(n) (say distorted speech) and a reference signal x(n) (say some signal which i...

## Wiener deconvolution and noise floor

Hello, I am using an example from one of my favorite statistical signal processing texts...

Hello, I am using an example from one of my favorite statistical signal processing texts (http://www.amazon.com/Statistical-Adaptive-Signal-Processing-Estimation/dp/1580536107/ref=sr_1_1?ie=UTF8&qid=1344697297&sr=8-1&keywords=kogon+adaptive+signal+processing). I don't know the page number or example off the top of my head, but I can find it if necessary. The problem d

## Karhunen-Loeve Expansion of a Wiener Process and Eigenvalues/Eigenfunctions of a Function

inWe covered KL expansion in my Random Processes course and in reviewing for the final I found that I'm really lost. Part of my problem is that...

We covered KL expansion in my Random Processes course and in reviewing for the final I found that I'm really lost. Part of my problem is that in performing the expansion you must find the eigenfunctions of a *function*. I don't understand that. The only place I've ever seen eigen-stuff is in linear algebra, and there we found the eigenvalues and eigen*vectors* of a square matrix. I've never...

## Wiener-Khintchin theorem, autocorrelation fundamentals

inHi, I am working on a summer project which requires basic knowledge of DSP, specifically I need to compute the Autocorrelation function (ACF)...

Hi, I am working on a summer project which requires basic knowledge of DSP, specifically I need to compute the Autocorrelation function (ACF) and PSD, which I have no problem computing. I am rather posting here to get some REASONING from the DSP and signal gurus about the basic theories of signals to expand my rather weak knowledge on DSP. I know that the ACF and PSD are fourier transform ...

## phase noise

inDear all, I am modelling phase noise for OFDM systems. At the receiver r=s*exp(j*phi)+w r= received signal s=transmitted...

Dear all, I am modelling phase noise for OFDM systems. At the receiver r=s*exp(j*phi)+w r= received signal s=transmitted signal phi=random phase w = AWGN noise I have studied in the literature that phase noise can be described as sampled version of wiener process, but for the purpose of analysis and simulations a discrete time random walk or weiner levy process is used. What exact...

## Adaptive filters

inHi I've read a book about adaptive noise reduction methods. I don't understand why the original signal (without noise) is needed in...

Hi I've read a book about adaptive noise reduction methods. I don't understand why the original signal (without noise) is needed in Wiener filtering, RLS filtering, LMS filtering... I mean, in most of the cases, you don't have any reference of the original signal when you want to reduce noise in a noisy signal! (otherwise, if you already know how the original signal is, why do you have to handl...