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autocovariance in matlab

Hi, I have a MATLAB related question. I have a periodic signal loaded into Matlab and i am trying to estimate the Autocovariance of it by using the xcov command. This gives me an output that i store as a variable. I'd just like to know if anyone knows why: a) the xcov matrix is twice as lon...

Re: Auto-correlation of white noise

On Aug 18, 9:44 am, "mr.t" wrote: > Im a beginner to signal processing so have that in mind. > > I know that the auto-covariance, c_v(k) of a white process, v(n), > is: > > c_v(k) = $_v^2 * D(k) > > Where $ is small-sigma and D is diracs deltafunction. > The auto-correlation in ...

Re: Scaling factor in inverse fourier transform

On 2007-04-10 07:15:28 -0300, cincydsp@gmail.com said: > On Apr 10, 5:06 am, "Titi Anggono" wrote: > > Hi all, > > > > I tried to calculate the autocorrelation from FFT using C. As far as I > > know the input for the inverse FT is the power spectrum density of the > > data X(t) > ...

Re: Prefered method for tone detection

This is just a suggestion. But a common form of detection (specially in beamforming) is to obtain the SVD decomposition of the autocovariance matrix of the data and create a detection paradigm based on the ratio of the largest to the lowest eigenvalues (or the ration of the geometric to arithm...

Re: filtering random processes

On 17 Jan, 00:22, "alex65111" wrote: > Let's assume on an input of the passband filter there is a complex white > noise. > > As on known spectral density on an input it is possible to calculate noise > level on an output of the passband filter? Yes it is. There is a standard resul...

Re: power spectrum density is always positive?

On 2006-09-27 08:54:04 -0300, Randy Yates said: > "Rune Allnor" writes: > > [...] > > If you are working on a theoretical justification, don't bring in the > > autocorrelation of x(t) since it has nothing to do with the > > *definition* > > of the PSD, it only describes and *esti...

Re: Correlated antenna gain

taqai@hotmail.com (taqai) wrote in message news: ... > If we have a transmitter antenna and M receiver antennas > then it is well known that by using maximum ratio combining > an M-fold improvement in the SNR can be obtained. > > But what if the receiver antennas are correlated and the ...

Re: A question about Covariance??

On 2006-06-02 07:24:55 -0300, "Rune Allnor" said: > > VijaKhara skrev: > > Dear members, > > For two Real Random Process X(t) and Y(t), the cross-covariance is Mean > > of ((X(t)-MeanX(t))(Y(t)-MeanY(t)). > > I learn that people calculate the correlation of two Random Process to >...

Re: non-stationary random process input to linear time variant system

On 3 Sep, 09:12, "misc" wrote: > Also I want to know if there is an analytical expression about the PSD of > the output when the system is LTV and input is non-stationary process. The only formal extension into the LTV systems and nonstationary signals is that you add another index in ...

Re: MLE : Random Vs Deterministic

On 31 Jan, 15:47, Mads Gr=E6sb=F8ll Christensen wrote: > I replied to a specific point you made about model selection. I informed > you that there are other ways than MDL, AIC, MAP, etc., that are less > restrictive than what you wrote. So your claim is that it is possible to determin...

Re: What can we expect by taking Fourier Transform of noise or random samples?

In article , "lucy" wrote: > Hi all, > > I am trying to understand using Fourier Transform to do denoising. > > I heard many times that people say suppose I have z(t)=y(t)+n(t), where z is > the observations of the useful signal y and n is the noise... then we can > look a...

Re: Comparing matched and Wiener filters

On 24 Des, 17:31, maury wrote: > On Dec 24, 5:12=A0am, Oliver Charlesworth wrote: > > My question is, what is the intuitive reason (i.e. not just "because th= e > > maths says so") why these don't end up with the same result, or more > > specifically, how the Wiener filter can mi...

Re: Simple Question on Random Variables and Random Processes

Randy Yates writes: > Randy Yates writes: > > > Let X(t) be a stationary white noise process with autocorrelation > > function R_{xx}(\tau) = N0 * \delta(\tau). Let V be a random variable > > determined from X(t) by > > > > V = \int_{-\infty}^{+\infty} X(t) dt. > > ...

Re: Analytic Functions and Single Side Band Signals

"Andor Bariska" wrote in message news:41c2cb13$1@news1.ethz.ch... > David Kirkland wrote: > ... > > Yup, a couple: > > 1) convolution in time = Multiplication in frequency = Addition in > > Ceptstrum (quefrency ?). > > David, > > do you know who invented these ridiculous t...

Re: PSD vs. Fourier transform

On 2009-03-01 12:03:04 -0400, Robert Adams said: > On Mar 1, 10:24 am, "m26k9" wrote: > > Hello, > > > > I have a confusion regarding Fourier transform of a time signal and the > > PSD. > > By definition, power spectral density (PSD) is the Fourier transform of > > the autoco...

Re: inverse of autocorrelation

On 2006-04-13 10:20:22 -0300, "Cagdas Ozgenc" said: > Greetings, > > Is it possible to recover a complex and periodic signal from its > autocorellation function (of course the result will be a time shifted > version, but it's OK)? If so, what's the inverse transformation. > > Th...

Re: parameters of sinusoid

Anton wrote: ... > Let's drop the state-space stuff (I hoped it would give me > a easier view on it...) and look at it this way: > > y[n] = a * y[n-1] + b * y[n-2] > > now I have a signal and I want to get to 'a' and 'b' from > a given set of samples 'y'. > As I said I guess I n...

Re: Deconvolution

On 7 Sep, 01:56, HardySpicer wrote: > If I have a random signal u(k) and a (known) transfer function H then > > y(k)=Hu(k) and if I know H and H is minimum phase then I ca neasily > find u(k). > > Suppose H is nonminimum phase eg > > y(k)=u(k)-2u(k-1) > > how to get at u(k)? C...

Re: Measurement Noise of PSD estimation (AR)

On 13 Jul, 17:07, "m.alwaieh" wrote: > Hallo, > > =A0I am quite new to this topic and I hope I can get some help here. > suppose we have a system driven by white noise resulting in a Random > Process. The measurement I get is the addition of the Random process with > the measurement n...

OFDM Autocovariance Channel Matrix for LMMSE channel estimation

Hello, I am testing different OFDM Channel estimation (CE) approaches by modelation in Simulink, and I am having a problem, that might be stupid but is taking to much of my time without finding a solution. My problem comes when I want to compare several methods to ideal LMMSE CE. I know the ch...

Re: Auto corelation

EC-AKD wrote: > Hi, > > Is there any optimised method to write auto corelation of any signal > in C. I was referring to AMR Speech codec's one of the auto corelation > function and found that it is too costly in terms of cycles it takes. > > Has anyone come up with any optimised ...

Spectrum of Wireless Channel with Exponential Power Delay Profile

A frequency selective Rayleigh fading channel is often modeled as having an exponential power delay profile. I've seen this written as pwr_dly(n) = exp(-tau*n/Ts) [1]. Tau here the rms delay spread (I think) and Ts is the sampling interval. I was wondering about the channel frequency response....

Re: how to understand projection, correlation & covariance

On 2009-04-08 09:49:46 -0300, Rune Allnor said: > On 8 Apr, 13:55, chenyong20...@gmail.com wrote: > > On 4月7日, 下午9时42分, Rune Allnor ntnu.no> wrote: > > > > > > > > > > > > > On 7 Apr, 15:16, chenyong20...@gmail.com wrote: > > > > > > H...

Rootmusic

This posting is a continuation of an earlier thread I was involved in. I wanted to continue with the old thread but found that re-posting wasn't possible. I guess the newsgroup world moves faster than me. I hope this post makes sense outside the original. The original thread can be found at -; ...

Re: Rootmusic

derrickrea@hotmail.com (Derrick Rea) wrote in message news: ... > Hi All, > > I'm trying to apply the Rootmusic algorithm, as found in Matlab, to > detect sinusoidal components in a blood velocity signal. > > I've synthesized a compound sinusoidal test signal that consists of 6 > si...

Re:

On 29 Aug, 18:38, "Michael Plante" wrote: > Also, for conditioning reasons, in the use of SVD, you are supposed to > doctor singular values that are very close to zero, with "close" being so= me > fraction (specific to the application) of the largest singular value. =A0= I do > not kn...

Re: Cross Correlation and Noise Reduction in Mic Arrays

Bob Cain wrote: > I'm looking at a problem involving an array of microphone > elements. The array is closely spaced, clustered within > less than half the wavelength of the highest frequency of > interest. > > The operations used to create outputs from this array is > differencing, ...

Re: Noise characterization of wavelet coefficients

"g" wrote in message news: ... > Hi, > > I hope this question about wavelets is not too far off topic in this > forum... > > I have some image data with noise for which the noise statistics (mean, > variance) are known : > > noisy image = true image + noise in image domain ...

Re: using lpc to interpolate

Kamran wrote: > Rune Allnor wrote: > > > > Kamran wrote: > > > > > Hi > > > > > > > > > Could anyone help me on how to use lpc (linear prediction coeff) > > > for interpolation ? I have a vector where some elements(samples) are way > > > off what is reasonable and wonder...

Re: confused about white noise definition

Les Cargill writes: > Randy Yates wrote: > > karl bezzoto writes: > > > > > Hello, > > > Per definition a white noise signal has a zero mean value. > > > > Really? By whos definition? Neither of two definitions I have found > > require the mean to be zero. I examine this que...

Re: what is lag-domain processing?

On 2006-04-21 08:00:27 -0300, "Rune Allnor" said: > > stereo skrev: > > Hello everyone, > > > > reading one of the classic papers about windowing, Nuttal's "Some > > Windows with Very Good Sidelobe Behaviour", I struggle with the > > sentence on page 86 "When the weighting is ap...

Re: UNDERSTANDING LINEAR PREDICTION AND AR FILTER

Muser wrote: > Hello All, > > I am having problem with understanding differences between AR Filtering > and linear prediction. They're the same thing, really. > I tried implementing linear prediction (using past values to predict the > present) using my own code, what i got for th...

Re: Optimal sampling for damped sinusoid

Rune Allnor wrote: > spasmous skrev: > > I am measuring a transient oscillating signal and have been wondering > > about the optimal sampling scheme to determine the decay and frequency. > > The model is S = A.exp(-Bt).sin(Ct) and I can sample about 5 points > > before the signal h...

Re: System Identification

On 30 Jun, 19:50, Vladimir Vassilevsky wrote: > Hello All, > > There is a physical system which is described well by the 2nd order pole > =A0 only model. The poles can be complex (Q up to 10), or real, including > the degenerated cases with one pole or no poles at all. The impulse > ...

Wiener filters for transient deconvolution

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 pul...

Re: Is White Noise Necessarily Zero-Mean?

I am going to discuss continuous-time random processes and white noise only. So, please do not muddy the waters by bringing in discrete-time white noise processes as obvious counterexamples for what I say below. For a second-order (i.e. finite variance) stationary random process, the autoco...

Re: Why minimising in the mean-error sense.

Bob Cain wrote in message news: ... > Matt Timmermans wrote: > > > > - Orthogonal transforms that preserve energy, like the Fourier transform, > > also preserve squared error. So if your goal is to minimize squared error, > > you can do it in the time or frequency domain and it w...

Re: Need help for some simple questions

doggie wrote: > > > Is it better to formulate the algorithm in the frequency domain or > time > > > domain and why? > > > > > > Using -y(k) =3D =E2=88=91wik x(k-i) > > > -e(k) =3D d(k) =E2=80=93 y(k) > > > -wik+1 =3D wik + 2=C2=B5e(k)x(k-i) > > > > > > or > > > > > >...