You get the following Matlab code from a fellow student: function [result]=what_do_i_do(x_vec_in,y_vec_in) a=min(x_vec_in); b=max(x_vec_in); dim1=length(x_vec_in); dim2=length(y_vec_in); if (dim1==dim2) n=10*dim1; x=[a:1/n:b]; y=interp1(x_vec_in,y_vec_in,x,'spline'); result 1/n* (0.5*(y(1)+y(end))+sum(y(2:end-1))); else sprintf('The input vectors are of different length!') result=NaN; end end When you call the function with two example input vectors the result will be what_do_i_do([0134],[0 19 16]) ans = 21.3338
You get the following Matlab code from a fellow student: function [result]=what_do_i_do(x_vec_in,y_vec_in) a=min(x_vec_in); b=max(x_vec_in); dim1=length(x_vec_in); dim2=length(y_vec_in); if (dim1==dim2) n=10*dim1; x=[a:1/n:b]; y=interp1(x_vec_in,y_vec_in,x,'spline'); result 1/n* (0.5*(y(1)+y(end))+sum(y(2:end-1))); else sprintf('The input vectors are of different length!') result=NaN; end end When you call the function with two example input vectors the result will be what_do_i_do([0134],[0 19 16]) ans = 21.3338
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter2: Equations And Inequalities
Section2.1: Equations
Problem 78E
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What is the purpose of this Matlab
a) Perform a non-linear regression based on a spline-function
b) Interpolate the data on an equidistant grid and perform a numerical
c) Solve an ordinary differential equation that is represented by data values on a non-equidistant grid
d) Determine the similarity of the two input
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