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0
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1answer
42 views

Calculating covariance matrix for MVDR beamforming

I am trying to calculate the covariance matrix that is required for the calculation of an MVDR beamformer. I am getting confused as to how to calculate it. I have an array of 3 microphones each with a ...
0
votes
0answers
42 views

Separating two mixed signals where one is constant (SVD/ICA)

I have two measurements m1 and m2 which contain a mix of two sources (signal + error). Typically this problem can be solved using SVD or Independent Component Analysis which will chose principal ...
1
vote
1answer
40 views

Relation between Covariance matrix & Energy of a random signal

Let's say I have the below random signal: $ Y[n] = [y(n), y(n-1), y(n-2), \ldots, y(1)] $ I have two random variables now: The first one $X_1 $ which express the maximum eigenvalue of the covariance ...
1
vote
1answer
52 views

Best way to find an object in a picture

I'm trying to find an object in a picture, my solution is to take the picture and a photo of the object and find the maximum of the mutual covariance, this is my ...
2
votes
1answer
34 views

Can I model process noise as a known “error” in my dynamics while designing a Kalman Filter?

Consider I am modelling the dynamics of a robot and using a Kalman filter to obtain estimates of some state. I have certain terms in my equation which correspond to data not accessible to this robot ( ...
2
votes
3answers
127 views

Variance of a filtered signal

I'm using a very simple 1st order Butterworth Filter shown in Matlab code: order = 1; cutOff = 0.1; [b, a] = butter(order, (2*cutOff)/SampleRate, 'high'); So ...
1
vote
2answers
80 views

PSD and $\lim_{T\rightarrow \infty} \frac 1 {2T} \int_{-T}^T x(t)\bar y(t)\,dt$

From Wikipedia, I taken a definition of power spectral density: For continued signals that describe, for example, stationary physical processes, it makes more sense to define a power spectral ...
0
votes
1answer
72 views

power spectral density plots

Hi all, How do we interpret a power spectral density plot. I have used modified covariance and burg methods and plotted using MATLAB. What does the peaks at some frequencies suggest? and what is the ...
2
votes
1answer
53 views

What is the technique to find variance of estimation error

Given an $n$-vector $y$ (responses) and a design matrix $X$, I wish to fit them with a simple linear regression model $$y=X\beta+e,$$ or, $y_t = x_t'\beta_0 + e_t$ where $e\sim\mathcal{N}(0, \sigma^...
2
votes
0answers
68 views

Distribution of a signal covariance matrix

A common estimation problem in signal processing assumes the following signal model \begin{equation} \mathbf{r} = \sum_{i=1}^{Q}\alpha_i\mathbf{s}\left(w_i\right)+\mathbf{n} \end{equation} where $\...
2
votes
1answer
201 views

What is a covariance matrix?

Suppose you have k samples from each of the N elements of a uniform linear array (ULA) of sensors: What is the physical meaning of a covariance matrix? How do you form a covariance matrix with the ...
0
votes
0answers
90 views

Problem calculating the average power of a vector?

I am calculating the average power of a vector. I would like to compare the final expression with the simulation. However, they are not equal. Please help me to point out which steps are wrong. Thank ...
1
vote
0answers
46 views

Solving an array signal processing estimation problem based on the Rayleigh quotient

The Rayleigh quotient for a covariance matrix $\mathbf{C}$ and a non-zero steering vector $\mathbf{a}$ is given by $$ R(\mathbf{C},\mathbf{a}) := \frac{\mathbf{a}^H\mathbf{C}\mathbf{a}}{\mathbf{a}^H\...
1
vote
1answer
199 views

Karhunen loeve transform question

I have read some about Karhunen-Loeve Transform (KLT) and its application to the field of seismic data processing. The method as I understand it based on decomposing the data (actually mostly used in ...
0
votes
0answers
235 views

Constant amplitude, uniform phase - what's the distribution of the complex signal then?

The well-known relationships for zero-mean circularly-symmetric complex Gaussian $z = a + jb = |z| \exp(j\varphi)$ signals are the amplitudes $|z| = \sqrt{a^2 + b^2}$ are Rayleigh-distributed the ...
3
votes
2answers
261 views

How to Extract Nonorthogonal PCA Principal Components

My problem is essentially a 'blind source separation' problem. I have 3 non-orthogonal sources (or basis functions) and $N$ random linear combinations (mixes) of said sources. My problem is to obtain ...
1
vote
1answer
182 views

Purpose of eigenspace of covariance matrix of a blob?

Given a blob of an image (representing an object), according to Wikipedia, we can compute the co-variance matrix using the image moments. I understand that the eigenvectors of that matrix can be used ...
0
votes
1answer
321 views

Error Propagation through an IFFT

I'm not sure how to approach this problem. I will describe what I am trying to do, and what some of my matlab outputs look like. I'm not trained in signal processing or anything, so please be ...
0
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0answers
92 views

Transfering the concept of time delay to image processing

I've just come across a paper that interrelates the covariance matrix of time discrete signals to their autocorrelation function (or a time-delay, respectively), i.e. $$\mathbf{C} = E\{\mathbf{x}\left(...
4
votes
2answers
459 views

Is there a way to reduce the covariance matrix of several source signals to the dominant source signal?

The problem I have can be seen in the context of DoA estimation or blind source signal separation and similar fields, where several source signals are observed by several antennas (or by an antenna ...
1
vote
2answers
438 views

Covariance matrix explanation

I am trying to understand and visualize the concept of a covariance matrix. Suppose I have a matrix: $A = \begin{pmatrix} 2 & 3 & 4\\ 5 & 5 & 6 \end{pmatrix}$ how do I calculate its ...
1
vote
1answer
575 views

information filter instead of kalman filter approach

I read many sources about kalman filter, yet no about the other approach to filtering, where canonical parametrization instead of moments parametrization is used. So I would like to learn on examples ...
0
votes
1answer
298 views

How do I find Gray Level Variance of the Image?

Tell me how do I find out gray level variance of the image? Is it any different from the normal variance of the image.
15
votes
1answer
661 views

How to tell if an error surface is convex? (Is it determined by the Covarinace matrix or the Hessian)?

I am currently learning about least-squares (and other) estimations for regression, and from what I am also reading in some adaptive algorithm literatures, often times the phrase "... and since the ...
7
votes
1answer
1k views

Question on covariance matrix of 2 spatial signals

Every time I think I have understood the covariance matrix, someone else comes up wih a different formulation. I am currently reading this paper: J. Benesty, "Adaptive eigenvalue decomposition ...
5
votes
1answer
1k views

Why does diagonal loading of a covariance matrix make an adaptive beamformer more robust in the case of a perturbed array?

It has been shown that 'diagonal loading' a covariance matrix derived for an adaptive beamformer can improve robustness of the beamformer when the antenna array is perturbed, albeit at the expense of ...