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Alternative to Orthogonal Matching Pursuit (OMP) Algorithm

In the Compressed Sensing context, assume there is a signal $ x \in {\mathbb{R}}^{n} $ which is $ k $ sparse. Namely its Pseudo $ {\ell}_{0} $ Norm is $ {\left\| x \right\|}_{0} = k $ (The signal has only $k $ non vanishing elements) where $ k << n…
Digi1
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Good Heuristic Point Where Sending FFT to GPU is Computationally Worth It?

This is a rather simple question, but I haven't found much posted within the last 5 years or so regarding a good rule of thumb for computing an FFT on the GPU vs the CPU. I know that most of the overhead of GPU-calculated FFTs is that you have to…
Scorch
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Coherent Sampling And The Distribution Of Quantization Noise

I have a question concerning the distribution of noise in the frequency domain in case of Coherent Sampling. I read up about Coherent Sampling and understood that in order for a frequency $f_{in}$ to be located on one single bin of the DFT, the…
MisterFilter
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Can deep learning be applied to video compression?

H.265 is based on incremental gains over time. The paradigms have largely remained the same. What are the odds of deep learning providing huge performance gains? Here is the main metric: Perceptual quality remains the same at 2x improvement in…
jkschin
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What is the tightest known bound on the reconstruction error in compressed sensing?

I am specifically thinking about the reconstruction error of L1-minimization from compressed measurements with noise. I know a bound from (8) in The restricted isometry property and its implications for compressed sensing, but I was wondering if…
Thomas Arildsen
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High audio frequencies in television broadcast

I would like to know if in television broadcast high end audio frequencies are transmitted e.g. frequencies higher than 14 kHz. What is the cut off audio frequency of transmission in television broadcast? I am preparing a report (for research)…
user3005720
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How to locally quantify the 'sharpness' of an image?

I am trying to quantify how much sharpness (or acutance) is in a picture which has some bokeh (out of focus background). I am using the Python scikit image for that. Here is my naive approach: import matplotlib.pyplot as plt from skimage import…
FZNB
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How to Prove a 2D Filter Is Separable?

I want to prove that 2D Gaussian filter is separable and we can separate it into two dimensions, my problem is about the size of filters. we should prove that $G(x,y)*I$(where $G(x,y)=$$\begin{bmatrix}0.01 & 0.1 & 0.01 \\0.1 & 1 & 0.1 \\ 0.01 & 0.1…
Panda
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Deriving the Matrix Inversion Lemma for RLS Equations vs the Woodbury Derivation

Can any one help me in deriving the matrix inversion lemma rule for RLS algorithm? I don't know how to start with. Many books have just stated but they haven't derived it.
Abhi
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Using reference objects to estimate the point spread function?

I have a well-defined object and a clear image matrix of it. In subsequent frames the object moves, causing motion blur. I want to use the object as a reference to "guide" the deconvolution and eliminate the motion blur. My idea is to use a…
Ktuncer
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Interpolation of magnitude of discrete Fourier transform (DFT)

For example for peak frequency finding, it seems valid to use band-limited interpolation methods on the complex DFT bins, or separately on their real and imaginary parts and to calculate the magnitudes or squared magnitudes of the results. But how…
Olli Niemitalo
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MP3 Decoding Discrepancy

Is it possible for two different decoders to output two different sample results for the same MP3? I'm decoding an mp3 on Matlab and it produces two columns (presumably one for each channel). When I extract the sample data from the same file using…
XSL
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Test data vs. training data

I am reading bishop book on pattern recognition and machine learning. Going through the introduction section, I am not sure if I get the differences between the two widely used term "test data" and "training data". Is training data the data you will…
Gigili
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2D Fourier Transform of Rotated Discrete Domain Signal

Assume we know that the Fourier transform of a signal $x(n_1,n_2)$ is $\mathcal{F}(x(n_1,n_2))=X(\omega_1,\omega_2)$. What is the Fourier transform of the signal after being transformed by a rotation matrix? I have found a property of the DFT that…
Josh
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Regarding the choice of cost function in adaptive control - squared error vs absolute error

I did search the question database regarding this question, and although one or two questions came close, they didn't really address my specific question. In adaptive control based on minimizing tracking error (e.g. between plant and model), the…
docscience
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