CyberMen
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Firstly, Matlab has a Built in Hough Transform: no need to reinvent the wheel. [H,T,R] = hough(BW,'RhoResolution',0.5,'Theta',-90:0.5:89.5); Although your image doesn't necessarily require edge ...

Effects of Averaging Using a moving average filter will smooth out the irregularities in the signal. The noise becomes E/N where N is the length of the moving average filter. The side effect of ...

While the above answer is really complete: Here is the gist of it: to downsample a signal it needs to be a whole number. Before the down sampling of a signal, you need to FILTER the signal. you can ...

on an ROC curve your plotting FP(x-axis) vs TP(y-axis) They are calculated by: True-positives = # of correctly detected positives/# of actual positives False-Positives = # of positives that are ...

Here are a few things that aren't right: 1) Regardless of the Carrier Synchronization: You are using 0 and 90 degrees for your signaling. You would need an I and Q channel in order to decode the ...

Typically Self tuning controllers are done in the digital domain. You may want to look into Least Squares Method for controller tuning.

If I am understanding this paper please correct me if I am wrong: A common effect, usually associated with unstable zeroes and poles of the open loop plant, makes it theoretically impossible to make ...

This is a no brainer for anyone who's studied signal processing (Im wondering why its been so long since its been answered) The Fourier Transform itself is a function that tells you what sinusoid do ...

It sounds like the OP is looking to align two signals. One simple way of caluclating this is to do something similar to the cross Corr: 1) Mark the left or right channel as the Reference channel 2)...

The area you're asking about is called "Onset Detection" this is used all throughout signal processing, but most oven used in Music Information Retrieval to identify the start and stop to notes. ...

If I am understanding what you're asking for, you're looking for an algorithm that uses the FT for image segmentation. 1) the FT will tell you where in your image is there a high frequency ...