Download presentation

Presentation is loading. Please wait.

Published byMckayla Burlingham Modified over 3 years ago

1
1 ECE310 – Lecture 20 Relationship between Signals - Correlation 04/11/01

2
2 Signal Relationship Orthogonality No relationship Correlation How much alike two signals are?

3
3 Orthogonality Orthogonality: the dot product of the two vectors is zero Continuous-time signals orthogonality - over some time range from t 0 to t 0 +T If signals x 1 (t), x 2 (t), … x n (t) are mutually orthogonal in some interval, then all the signals are linearly independent in the interval, or none of the signal can be represented as a linear combination of others.

4
4 Correlation An analysis of whether two signals tend to “move together” Classification Highly correlated Highly positive correlated – over a long period of time, the signals tend to move in the same direction at the same time Highly negative correlated – over a long period of time, the signals tend to move in the opposite directions at the same time Partially correlated Uncorrelated – over a long period of time, the two signals tend to move in the same direction about half the time and in opposite directions the other half of the time Correlogram (with the two signals as the two axes) Correlation is a number

5
5 Correlogram Examples

6
6 % Function: Demonstrate the correlation between signals and the corresponding correlograms, correlation number % Author: Hairong Qi % Date: 04/08/01 clear all; clf; t = 0:0.01:1; % uncorrelated y1 = sin(2*pi*t); y2 = cos(2*pi*t); subplot(341); plot(t, y1); title('sin(2*pi*t)'); % signal 1 subplot(345); plot(t, y2); title('cos(2*pi*t)'); % signal 2 subplot(349); plot(y1, y2, '*'); xlabel('y1'); ylabel('y2'); % the correlogram % sum(y1.* y2) is the correlation number. sprintf() is the output reformat, and corrnr is a string corrnr = sprintf('UC: %5.2f', sum(y1.* y2)); title(corrnr); % highly negative correlated y1 = sin(2*pi*(t-1/4)); % signal 1 shifted to the right by 1/4 y2 = cos(2*pi*t); subplot(342); plot(t, y1); title('sin(2*pi*(t-1/4))'); subplot(346); plot(t, y2); title('cos(2*pi*t)'); subplot(3,4,10); plot(y1, y2, '*'); xlabel('y1'); ylabel('y2'); corrnr = sprintf('HNC: %5.2f', sum(y1.* y2)); title(corrnr); % highly positive correlated y1 = sin(2*pi*(t+1/4)); % signal 1 shifted to the left by 1/4 y2 = cos(2*pi*t); subplot(343); plot(t, y1); title('sin(2*pi*(t+1/4))'); subplot(347); plot(t, y2); title('cos(2*pi*t)'); subplot(3,4,11); plot(y1, y2, '*'); xlabel('y1'); ylabel('y2'); corrnr = sprintf('HPC: %5.2f', sum(y1.* y2)); title(corrnr); % partially correlated y1 = sin(2*pi*(t-1/3)); % signal 1 shifted to the right by 1/3 y2 = cos(2*pi*t); subplot(344); plot(t, y1); title('sin(2*pi*(t-1/2))'); subplot(348); plot(t, y2); title('sin(2*pi*t)'); subplot(3,4,12); plot(y1, y2, '*'); xlabel('y1'); ylabel('y2'); corrnr = sprintf('PC: %5.2f', sum(y1.* y2)); title(corrnr); Posted on web

7
7 Correlation Function Autocorrelation and crosscorrelation Correlation function is the correlation (number) when one signal is shifted across the other

8
8 Autocorrelation Function Correlation of a function with itself When shift t=0 When shift != 0 Therefore, ???

9
9 Correlation Function of Energy and Power Signals Energy signal Power signal

10
10 Correlation Function of Two Periodic Signals T 0 is the period of the product, i.e. the LCM of T x and T y

11
11 Discussion The representation of a signal by a Fourier series can be seen as a process of correlating the signal with the sinusoids or complex exponentials to find out whether any particular sinusoid or complex exponential is present in the signal, and if so, how much of it is there. In another word, the coefficients calculate a “weight”

Similar presentations

OK

MATLAB BASICS ECEN 605 Linear Control Systems Instructor: S.P. Bhattacharyya.

MATLAB BASICS ECEN 605 Linear Control Systems Instructor: S.P. Bhattacharyya.

© 2018 SlidePlayer.com Inc.

All rights reserved.

To ensure the functioning of the site, we use **cookies**. We share information about your activities on the site with our partners and Google partners: social networks and companies engaged in advertising and web analytics. For more information, see the Privacy Policy and Google Privacy & Terms.
Your consent to our cookies if you continue to use this website.

Ads by Google

Ppt on marie curie's accomplishments Ppt on power generation by speed breaker sign English 8 unit 12 read ppt on iphone Ppt on 21st century skills rubric Ppt on social media past present and future Ppt on english grammar in hindi Ppt on plants for grade 2 Ppt on special types of chromosomes based Ppt on ms excel tutorial Ppt on p&g products coupon