Convolution on a nonlinearly spaced data set.

14 次查看（过去 30 天）
Senaasa
Senaasa 2013-6-29
Hi,
I am currently trying to use conv on a data set that is nonlinearly spaced. The convolution works, the issue I'm having is reproducing the amplitude of the convolution signal. For example, if it were a linearly spaced dataset I'd use u = conv(h,f)*dt; where dt is the spacing between points.
In my case I don't have a consistent dt value since it varies. Any suggestions on how to approach this? Thanks, Charles
  2 个评论
Matt J
Matt J 2013-6-29
编辑：Matt J 2013-6-29
In what way does the convolution "work", as you have it so far, if you aren't yet accounting for the varying sample spacing? And is there a reason you don't just apply interp1() and resample the signals so that they are equi-spaced?
Senaasa
Senaasa 2013-6-29
It works insofar that the profile of the convolution is correct, but the amplitude is incorrect. I had been using a loop to calculate the convolution so I have a comparison. Interpolating is possible, however I wanted to use conv to try to speed up my convolutions. If I have to interpolate and add points (in this case probably several thousand), I'm not sure how much of a benefit I'd gain by using conv. I was hoping there was a cleaner way just through the implementation of conv.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Image Analyst
Image Analyst 2013-6-29
Like Matt J says, the usual solution is to get evenly spaced intervals using interpolation, such as interp1() or spline().
Here's a spline demo if you want to do a cubic fit between the points:
% Demo to show spline interpolation.
% Clean up / initialize
clc;
close all;
clear all;
workspace; % Display workspace panel.
% Create the original knot points.
lengthX = 10;
x = 1:lengthX;
y = rand (lengthX,1);
% Plot it and show how the line has sharp bends.
plot(x, y, '-sr', 'LineWidth', 2);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
% Use splines to interpolate a smoother curve,
% with 10 times as many points,
% that goes exactly through the same data points.
samplingRateIncrease = 10;
newXSamplePoints = linspace(1, lengthX, lengthX * samplingRateIncrease);
smoothedY = spline(x, y, newXSamplePoints);
% Plot smoothedY and show how the line is
% smooth, and has no sharp bends.
hold on; % Don't destroy the first curve we plotted.
plot(newXSamplePoints, smoothedY, '-ob');
title('Spline Interpolation Demo', 'FontSize', 20);
legend('Original Points', 'Spline Points');
% Mathworks Demo code from their Help
% x = 0:10;
% y = sin(x);
% xx = 0:.25:10;
% yy = spline(x,y,xx);
% plot(x,y,'o',xx,yy)
The input points don't need to be uniformly spaced like I did in the demo.

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Spline Postprocessing 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by