Questions tagged [sparse-model]
The sparse-model tag has no usage guidance.
16
questions
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1answer
34 views
Is it common to impose the sparsity on the Fourier coefficient itself?
In compressive sensing, I see many works to impose the sparsity on the wavelet coefficients (e.g., by minimizing the L1 norm of such coefficients.) Another example in MRI is to impose sparsity on the ...
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vote
0answers
83 views
A hypercomplex encoding to preserve spatial/temporal information? [closed]
I have recently come across the idea of encoding a 1D signal (i.e. a mono audio) as a complex vector instead of as a vector of reals, where the imaginary part is used to encode the cells' positions. ...
2
votes
1answer
63 views
Solving LASSO (Basis Pursuit Denoising Form) with LARS
I'm now working on using LARS (Least Angle Regression) algorithm to solve a LASSO problem in Basis Pursuit Denoising form like:
\begin{align*}
\quad && \arg \min_{\beta}{\left\| y - X\beta \...
1
vote
0answers
17 views
Solving Sparse Model with given Dictionary Using LASSO
I was trying to solve a problem where the basis matrix contains the components of $\sin(nx)$, $\cos(nx)$, $\sinh(nx)$ and $\cosh(nx)$.
Say the $n$ varies from 1 to 100. While solving the lasso linear ...
2
votes
1answer
62 views
Implementation of Block Orthogonal Matching Pursuit (BOMP) Algorithm - Fix Given Code [closed]
This is my implementation which doesn't work:
...
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2answers
196 views
Implementation of Block Orthogonal Matching Pursuit (BOMP) Algorithm [closed]
How would one implement the Block Orthogonal Matching Pursuit (BOMP) Algorithm in MATLAB?
2
votes
2answers
180 views
Constrained LASSO Problem - $ {L}_{1} $ Regularized Least Squares with Linear Equality Constraints
I have an optimization question.
I want to solve the following problem:
$$
\arg\min_S\frac{1}{2}\|s-c\|_2^2 +\lambda\|\Phi s\|_1 \mbox{ s.t. } As = 0
$$
in which $\Phi$ is the wavelet transform ...
0
votes
0answers
35 views
Implementation of PCA for hyper-spectral Image Processing
I have been studying the concept of PCA and its implementation for dimensionality reduction for more than 1 month. My goal is to classify a hyperspectral image using sparse representation by the ...
3
votes
4answers
335 views
Estimate peak width from a vector that is a superposition of unknown number of identical Gaussian peaks with different heights?
If you have a vector that is a superposition of an unknown number of identical Gaussian shaped peaks/impulses of unknown width (but all the same width) and different amplitudes (with Poisson or ...
4
votes
2answers
156 views
Is There a Sparse Representation for Noise?
Is there sparse representation for stationary noise and nonstationary noise?
How can I learn dictionary for each noise class?
(my mean of noise is noises with which speech signals are often ...
2
votes
2answers
140 views
Compressive Sensing and Sparsity
We apply compressive sensing to reconstruct a signal if it is sparse in the original domain or has a sparse represetation in some basis.
How we may know a if a signal is sparse or has a sparse ...
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2answers
847 views
Ifft through Matrix multiplication
I am still new to MATLAB, so apologies if I sound lazy to you. I am attempting to model a transformation as a set of matrix operations. I start with a vector, up-sample it by $U$ (up-sampling rate), ...
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2answers
214 views
How to make the impulse response sparse? How does one know that the channel is sparse?
I am new to sparse channel estimation algorithms and reading research articles. One such paper is blind sparse channel estimation using a modification of the BOMP technique titled, "Blind Acoustic ...
1
vote
2answers
679 views
When can the impulse response become zero?
The article Efficient Use Of Sparse Adaptive Filters (Proc. Asilomar Conference, Khong et al., 2006) introduces adaptive filters for the estimation of channels or systems having a sparse impulse ...
3
votes
1answer
335 views
Why Sparse Priors Like Total Variation Opts to Concentrate Derivatives at a Small Number of Pixels?
When performing image deconvolution (deblurring), people often make use of priors to get rid of the illness of the problem. One very common prior is total variation, a sparse prior. Compared to ...
8
votes
3answers
1k views
DCT and Hard Thresholding
If I have an Image and i find the DCT and then apply hard thresholding on the coefficients and then IDCT then I have attenuated the noise. Can someone please explain in detail or point me to the ...
