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Questions tagged [sampling]

In signal processing, sampling is the reduction of a continuous-domain signal to a discrete-domain signal.

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Why is oversampling helpful to an anti-alias filter?

Why does oversampling make the job of an anti-alias filter easier? I don't understand the intuition on why it becomes helpful. Isn't it economical to just keep the sampling rate at the minimal level,...
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1answer
634 views

How do I resample an image to a rotated grid?

I have an image, I, sampled on a uniform grid: $\ x_i = i*\Delta x, y_j = j*\Delta y, $ I need to resample this image to a grid rotated counterclockwise by an angle $\ \theta$ around $\ (x_0,y_0)$: ...
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212 views

Locking on to a square wave signal with minimum oversampling

I'm designing a device that will have an IR photodiode connected to a low power microcontroller's ADC pin. At times, another device will be transmitting a 48KHz square wave, and I'd like to be able to ...
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952 views

Matlab BOC (binary offset carrier)

I am trying to implement a binary offset carrier (BOC) direct sequence spread spectrum scheme in MATLAB. In that scheme, a code $c(t)$ (a binary vector which repeats after a certain number of zeros ...
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Sampling of a continuous function: Kronecker's or Dirac's delta?

I've been reading some papers in signal proccesing and I'm very confused about the issue in the title of my question. Consider a continuous function of time $t$, $f(t)$, that I sample at uneven times $...
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4answers
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How does the quantization error generate noise?

I'm learning about sampling and DSP on my own. I have a hard time to understand how the quantization error results in noise. I think I miss a fundamental understanding but can't tell what it is. So ...
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2answers
649 views

determine two signals with a scale factor

Suppose I have 2 signals from function $f_1(x)$ and $f_2(x)$, respectively, and assume the sampling rate is above Nyquist frequency, so we can restore the underlying functions $f_1(x)$ and $f_2(x)$. ...
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Is there such a thing as band-limited non-linear distortion?

So if you generate a square wave by just switching a signal between two values, at sample boundaries, it produces an infinite series of harmonics, which alias and produce tones below your fundamental, ...
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Alias frequency Formula

I'm taking a multimedia systems class in my MSc Computer Science, and I'm having some trouble understanding the formula for the alias frequency - this could stem from my misunderstanding of the alias ...
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2answers
288 views

If sampling rate is high does that increase the error or decrease the error?

Suppose we are tracking a computer mouse on the screen, if we increase the frequency of the sampling rate(to very high values) then would that increase the error in getting the exact position of the ...
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Directly compare subpixel shifts between two spectra — and get believable errors

I have two spectra of the same astronomical object. The essential question is this: How can I calculate the relative shift between these spectra and get an accurate error on that shift? Some more ...
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3answers
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Demonstrating the effect of aliasing

How does the signal look when we don't use the Nyquist rate to remove aliasing from a signal during sampling? Let's suppose the signal is sinusoidal, with a frequency of 500 Hz and an amplitude ...
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1answer
885 views

What is “Equivalent Time Sampling” and what is it good/used for?

The literature on this method seems scarce, but I know that it has been used on radar systems to 'get away with' not having to sample nearly as fast as Nyquist would otherwise dictate, (at the cost of ...
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1answer
117 views

What is the difference between the Point Spread Function and Sampling Aperture?

I've been told that the point spread function of a pixel is its distribution of intensity, while the sampling aperture of a pixel is its distribution of sensitivity. I'm a little unsure of what the ...
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1answer
515 views

Reference for Supersampling

I want to downsample images to arbitrary sizes using supersampling to avoid aliasing effect. The only two good explanations I found were on Wikipedia and everything2.com, but there are still gaps. ...
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2answers
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Compensating for measurement errors

I have a system where I sample some data periodically (every 10usec). The shape of the data is triangle, in other words it linearly increases and decreases in time. (Both theory and practice are in ...
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The current state of the art in audio signal interpolation

Three questions: What are all the metrics one can use to measure audio interpolation quality, objectively? (but also in terms of psychoacoustics if possible) By those metrics, what is the current ...
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3answers
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“Complex sampling” can break Nyquist?

I have heard anecdotaly that sampling complex signals need not follow Nyquist sampling rates but can actually be gotten away with half Nyquist sampling rates. I am wondering if there is any truth to ...
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1answer
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How to determine where to sample for demodulation of BPSK signals?

I have a simple BPSK demodulator. Very simply, the signal comes in and is split into two branches, one for I and one for Q. The I branch is mixed with a sin wave of the carrier, and the Q branch ...
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2answers
258 views

Is there any way to make a sampling rate reduction in the frequency domain?

Is there any way to take advantage of the frequency domain to make a clean/nice sampling rate reduction effect ? and how ? Basically, deducted from my tests: if I set to 0 the magnitude uppon a ...
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3answers
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What is anti-alias pre-filter for preventing aliasing after under-sampling?

We know that the under-sampling results in aliasing and frequencies higher than half of the Nyquist rate is not distinguishable. I've a base band signal that I want to use the higher frequencies which ...
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1answer
156 views

What is the smallest sampling points that can recover the signal?

Propose that we have a signal with a model of $$ f_{4at0} = v_0(1 - \epsilon + \epsilon \exp(-c_l(t_{t2d}-t_0))) $$ $f_{4at0}$ is dependent variable while $t_{t2d}$is independent variable,others ...
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2answers
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Downsampling an image by an integer factor

When downsampling an image by an integer factor $n$, the obvious method is to set the pixels of the output image to the average of the corresponding $n \times n$ blocks in the input image. I remember ...
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3answers
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What is the effect of aliasing on the magnitude of the autocorrelation?

I've a question about the effect of aliasing on the magnitude of autocorrelations. From a simulation in MATLAB, I don't see any effect of aliasing or any need to anti-alias filter when I take the ...
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5answers
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FIXED POINT conversion Problem (DSP)

Actually after reading the data from ADC is an $Q15$ format (ie. ADC supports 0-3.3v, ADC is an unipolar type). then the $Q15$ data is converted to $q31$ format ($Q31$ value = $q15_{data}$ <<16)....
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5answers
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When is aliasing a good thing?

In Hamming's book, The Art of Doing Science and Engineering, he relates the following story: A group at Naval Postgraduate School was modulating a very high frequency signal down to where they ...
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3answers
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What are the advantages, if any, of derivative sampling?

In Five short stories about the cardinal series $[1]$, the author makes the following comment: Interestingly enough, Shannon goes on to mention that other sets of data can also be used to ...
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4answers
13k views

How do I extrapolate a 1D signal?

I have a signal of some length, say 1000 samples. I would like to extend this signal to 5000 samples, sampled at the same rate as the original (i.e., I want to predict what the signal would be if I ...
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1answer
7k views

What is meant by “stochastic sampling”?

What exactly is meant by "stochastic sampling" and is it profoundly different from the regular Nyquist-Shannon sampling theorem? Is it related to sampling a stochastic process?
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5answers
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Why would I leave a signal oversampled?

I can't think of a better way for asking this question so I will start with an example. Suppose that I have an input signal with a max frequency of 50Hz (sampled at 100Hz). Now the signals of interest ...