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1answer
34 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 ...
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0answers
57 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 ...
2
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2answers
73 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
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1answer
65 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
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1answer
107 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 ...
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0answers
76 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} = ...
4
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2answers
150 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 ...
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2answers
179 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
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1answer
260 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
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1answer
172 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.
13
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1answer
295 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
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1answer
654 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
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1answer
386 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 ...