Difference between revisions of "Convolution"
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'''Description:''' Convolution is used mostly for signal and systems analysis. It is a way to combine two time series. This model contains function Convolve(Y, Z, T, I), that computes the convolution of two time series. The model contains several examples of convolved functions. | '''Description:''' Convolution is used mostly for signal and systems analysis. It is a way to combine two time series. This model contains function Convolve(Y, Z, T, I), that computes the convolution of two time series. The model contains several examples of convolved functions. | ||
Latest revision as of 08:27, 17 January 2023
Example model
Description: Convolution is used mostly for signal and systems analysis. It is a way to combine two time series. This model contains function Convolve(Y, Z, T, I), that computes the convolution of two time series. The model contains several examples of convolved functions.
A time series is a set of points, (Y, T), where T is the ascending X-axis, and the set of points is indexed by I. The values of T do not have to be equally spaced. The function treats Y and Z as being equal to 0 outside the range of T. The two time series here are the set of points (Y, T) and the set of points (Z, T), where both sets of points are indexed by I.
The mathematical definition of the convolution of two time series is the function given by:
- [math]\displaystyle{ h(t) = \int y(u) z(t-u) dt }[/math]
Keywords: Signal analysis, systems analysis
Author: Lonnie Chrisman
Download: Convolution.ana
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