44 votes
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The difference between convolution and cross-correlation from a signal-analysis point of view

In signal processing, two problems are common: What is the output of this filter when its input is $x(t)$? The answer is given by $x(t)\ast h(t)$, where $h(t)$ is a signal called the "impulse ...
MBaz's user avatar
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21 votes

The difference between convolution and cross-correlation from a signal-analysis point of view

The two terms convolution and cross-correlation are implemented in a very similar way in DSP. Which one you use depends on the application. If you are performing a linear, time-invariant filtering ...
Peter K.'s user avatar
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11 votes

Fast pitch recognition

"Is there a way to measure frequency (detect pitch) better than FFT, that is, with better resolution in less acquisition time?" yes there is. or are. there are multiple better ways to do ...
robert bristow-johnson's user avatar
11 votes

Understanding the Difference Between MAP Estimation and ML Estimation

Maximium A Posteriori (MAP) and Maximum Likelihood (ML) are both approaches for making decisions from some observation or evidence. MAP takes into account the prior probability of the considered ...
Mark Borgerding's user avatar
10 votes

The difference between convolution and cross-correlation from a signal-analysis point of view

@MathBgu I have read all above given answers, all are very informative one thing I want to add for your better understanding, by considering the formula of convolution as follows $$f(x)*g(x)=\int\...
RM Faheem's user avatar
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9 votes

A Machine Learning Based Algorithm as an Alternative to the Matched Filter

Sure, you can learn the matched filter, as convolution with a filter is just a function applied to a signal, and e.g. Neural Networks (through the universal approximation theorem) are good function ...
Marcus Müller's user avatar
8 votes
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Signal Estimation after detection Part 2

After signal detection, how to estimate the clean signal $s(t)$? Matched filtering is used to detect the presence of a known signal in noise. There is no estimation part when you are talking about a ...
Engineer's user avatar
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7 votes

Estimators for improved spectral subtraction of noise

Maximum likelihood (ML) estimator Here will be derived a maximum-likelihood estimator of the power of the clean signal, but it doesn't seem to be improving things in terms of root mean square error, ...
Olli Niemitalo's user avatar
7 votes

Amplifier Placement in a Wireless Receiver

Placing the amplifier first will result in a lower noise figure for the receiver and hence more sensitivity but the amplifier will be exposed to all of the ingested signals, including undesired ...
GrapefruitIsAwesome's user avatar
7 votes
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Identify abrupt changes in an audio waveform

Synchrosqueezed Wavelet Transform is an option. I have developed a complete algorithm for this task, which scores 100% train accuracy and 86% test accuracy with 0.05 sec tolerance, without machine ...
OverLordGoldDragon's user avatar
6 votes

Understanding the Difference Between MAP Estimation and ML Estimation

You have a set of message set $m_i$, $0 \le i \le N-1$. (For example, QPSK will be $N=4$). For the transmitted message $m_i$, the corresponding symbol vector is $\textbf{x}_i$, and the received symbol ...
jithin's user avatar
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6 votes

How to decide whether a recording contains a signal of interest?

Is it possible to decide based on the result of the cross-correlation whether a recording contains the signal of interest? Certainly. The easiest way would be look at the crest factor (peak to RMS ...
Hilmar's user avatar
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5 votes

suppose if we send AM modulated message signal through space how the receiver will be knowing that we applied AM modulation?

Communications systems are always designed under the assumption that both emitter and receiver know what "language" they will be speaking to each other. AM modulation comms are standardized in ...
MaximGi's user avatar
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5 votes

The difference between convolution and cross-correlation from a signal-analysis point of view

There is a lot of subtlety between the meanings of convolution and correlation. Both belong to the broader idea of inner products and projections in linear algebra, i.e. projecting one vector onto ...
orodbhen's user avatar
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5 votes

Recovering signal for psk

To add to the excellent information given by Cassman in his response, here is a block diagram of a carrier recover loop for QPSK and QAM modems using a decision directed approach. I have detailed the ...
Dan Boschen's user avatar
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5 votes
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Radar Pulse Compression Gain (PCR)

The answer is yes but one has to specify $B_n$ properly to avoide possible confusions. In case if one uses a pulse compression, the bandwidth through which the receiver collects the noise will ...
kda's user avatar
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5 votes

Expectation of deterministic signals

If $x(t)$ is a deterministic signal, then you have $E[x(t)]=x(t)$. Furthermore, if $Y(t)$ is a random process you have $E[x(t)Y(t)]=x(t)E[Y(t)]$.
Matt L.'s user avatar
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5 votes

Estimators for improved spectral subtraction of noise

Update: I'm sorry to have to say that testing shows the following argument seems to break down under heavy noise. This is not what I expected, so I have definitely learned something new. My prior ...
Cedron Dawg's user avatar
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5 votes
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Maximum likelihood estimation complexity computation

Ordinary Least Squares problem Your $$\hat x = \arg\min_x \sum_{n=1}^{N_r} \left\lvert y_n - h_n x\right\rvert^2$$ is just a way of saying $$\hat x = \arg\min_x \left\| y - Hx \right \|$$ and that is ...
Marcus Müller's user avatar
5 votes
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How would you use machine learning for peak detection?

To be honest, I don't think CNNs, RNNs and LSTM are useful for this kind of problem – a bandpass filter followed by a threshold would be. Now, that would have three parameters: Lower cutoff ...
Marcus Müller's user avatar
5 votes
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Testing if a signal contains a specific previously recorded signal

This does sound like a job for cross correlation. It's quite robust and some tweaking with the threshold value should give you the result you are looking for. It's calculated in the time domain, so no ...
Max's user avatar
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5 votes
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The power of signal processing when faced with hardware constraints

That's a very broad question, but I'll give it a shot. 1 . ... how much could signal processing actually do to help us here ? ... That's highly dependent on the specific problem. Sometimes a lot, ...
Hilmar's user avatar
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4 votes

Detecting a Signal Inside a Time Series Using MATLAB's $ \tt xcorr() $

It is usually useful to use normalized cross-correlation for finding position of small template on other longer signal. The value of normalized cross-correlation coefficient is invariant to change of ...
SergV's user avatar
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4 votes

Fast pitch recognition

I already answered your question here: https://stackoverflow.com/questions/33667275/fast-frequency-measurement/33678202#33678202 But, in summary, in certain circumstances, you can interpolate an FFT ...
hotpaw2's user avatar
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4 votes
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Pulse Compression(Chirp) SNR Gain

It's often said that pulse compression gives you a gain proportional to the time-bandwidth product (otherwise known as the pulse compression ratio, or $PCR$). This is a really misleading statement, ...
Beepboop bebop's user avatar
4 votes
Accepted

Finding Reference Audio Signal in Test Audio Signal and Cropping Accordingly

If you have a reference signal you want to find in a different signal then your model matches almost perfectly (Up to the environment the signal to be found is in) to Matched Filter. So basically you ...
Royi's user avatar
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4 votes

How Can Telecommunication System Know Which Part Is Signal and Which Is Noise?

To elaborate on MM's answer just a little bit. Unless the receiver has some sort of expectation of the nature of the signal there is no way to tell. With an expectation (for instance a pure tone), ...
Cedron Dawg's user avatar
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4 votes

Preamble Detection and Frequency Offset Estimation in radio packets

For maximum sensitivity preamble detection with time referencing, consider using a barker code, or for more choices with longer lengths a PRN (pseudo-random noise) sequence, or for even more choices ...
Dan Boschen's user avatar
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4 votes
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SVD vs matched filter

That's not true, it's not better. The thing is: the matched filter just implements the projection in the signal vector space, onto the signal vector itself (or a multiple thereof). (You'll find ...
Marcus Müller's user avatar
4 votes

Autocorrelation function of a triangular wave

I couldn't quite follow your code (you calculate two different versions of the ACF?), but I believe the problem with the plot being shifted toward zero is that xcov ...
Engineer's user avatar
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