How can I plot this state space like the graph I attached by using tf() and step() command? Thank you! I2/E0=1/(s^3+s^2+3*s+1) NOTE:- Matlabsolutions.com provide latest MatLab Homework Help, MatLab Assignment Help , Finance Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research. Try these codes below please; clc; clear; close all; numerator = 1; denominator = [1,1,3,1]; sys = tf(numerator,denominator); yyaxis left SEE COMPLETE ANSWER CLICK THE LINK https://www.matlabsolutions.com/resources/how-to-plot-transfer-functions-in-matlab-.php
I'm trying to do hierarchical clustering in MATLAB using 'linkage' and 'pdist' functions. I'm familiar with the functions, but I'm attempting to cluster by the absolute value of the correlation values.
The default for the 'pdist' function, 'correlation', would include both the positive and negatives, but I'm interested in grouping inverse relationships as well.
Does anyone know how I can achieve this?
NOTE:-
Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help , Finance Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.
There are two ways in which this can be done:
First, notice that 'pdist' computes one minus the correlations among rows:
>> x x = 1 2 3 4 2 3 2 3 1 2 3 4 4 3 2 1 >> pdist(x,'cor') ans = 0.5528 0 2.0000 0.5528 1.4472 2.0000 >> 1-corr(x') ans = 0 0.5528 0 2.0000 0.5528 0 0.5528 1.4472 0 0.5528 0 2.0000 2.0000 1.4472 2.0000 0
1) The first way is to compute the distance as one minus the absolute correlation, and compute linkage based on that.
>> D = pdist(x,'cor'); >> linkage(D,'single') ans = 1.0000 3.0000 0
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