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Numerical Integration - Constant Increment The area under a curve can be estimated by breaking the x axis into increments, evaluating the function at a point inside that increment, and approximating the area under the curve in that increment as a rectangle. The figure below shows this approximation with an increment of 1 and the function being evaluated at the midpoint of the increment. 20 18 L 1.5 2 16 14 12 10 8 6 4 Script Given a range (upper and lower limits) and increment, use the midpoint approximation as shown above to estimate the area under the curve: y = x² + 2x In(x) You can assume that the increment given will evenly divide the range. 2.5 - 3 35 1 %% Variables to be used 2% Inputs 3% Xmin the minimum limit of the range 4% Xmax the maximum limit of the range. 5% inc the increment for the numerical approximation 6 7 % Outputs Save C Reset My Solutions > 8% area the final approximation of the area under the curve for the given range 9 10 %% Inputs 11 % This generates the scalars, Xmin, Xmax, and inc, with random values which will be used to evaluate your code 12 Xmin=randi(10)+1 13 inc=randi (3) 14 Xmax=Xmin+inc*(randi(8)+2) 15 16 %% Program 17 % Start writing your program here. MATLAB Documentation.

Numerical Integration - Constant Increment The area under a curve can be estimated by breaking the x axis into increments, evaluating the function at a point inside that increment, and approximating the area under the curve in that increment as a rectangle. The figure below shows this approximation with an increment of 1 and the function being evaluated at the midpoint of the increment. 20 18 L 1.5 2 16 14 12 10 8 6 4 Script Given a range (upper and lower limits) and increment, use the midpoint approximation as shown above to estimate the area under the curve: y = x² + 2x In(x) You can assume that the increment given will evenly divide the range. 2.5 - 3 35 1 %% Variables to be used 2% Inputs 3% Xmin the minimum limit of the range 4% Xmax the maximum limit of the range. 5% inc the increment for the numerical approximation 6 7 % Outputs Save C Reset My Solutions > 8% area the final approximation of the area under the curve for the given range 9 10 %% Inputs 11 % This generates the scalars, Xmin, Xmax, and inc, with random values which will be used to evaluate your code 12 Xmin=randi(10)+1 13 inc=randi (3) 14 Xmax=Xmin+inc*(randi(8)+2) 15 16 %% Program 17 % Start writing your program here. MATLAB Documentation.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Numerical Integration - Constant Increment The area under a curve can be estimated by breaking the x axis into increments, evaluating the function at a point inside that increment, and approximating the area under the curve in that increment as a rectangle. The figure below shows this approximation with an increment of 1 and the function being evaluated at the midpoint of the increment. 20 y 18 16 14 12 > 10 8 6 4 0 0.5 1 Script> 1.5 1 2 X 2.5 3 3.5 Given a range (upper and lower limits) and increment, use the midpoint approximation as shown above to estimate the area under the curve: x² + 2x In (x) You can assume that the increment given will evenly divide the range. 4 1% Variables to be used 2% Inputs 3 % Xmin the minimum limit of the range 4% Xmax - the maximum limit of the range 5 % inc the increment for the numerical approximation Save C Reset My Solutions > 6 7 % Outputs 8% area - the final approximation of the area under the curve for the given range 9 10% Inputs 11% This generates the scalars, Xmin, Xmax, and inc, with random values which will be used to evaluate your code |12 Xmin=randi(10)+1 13 inc=randi(3) 14 Xmax=Xmin+inc×(randi(8)+2) 15 16 % Program 17% Start writing your program here MATLAB Documentation
Transcribed Image Text:Numerical Integration - Constant Increment The area under a curve can be estimated by breaking the x axis into increments, evaluating the function at a point inside that increment, and approximating the area under the curve in that increment as a rectangle. The figure below shows this approximation with an increment of 1 and the function being evaluated at the midpoint of the increment. 20 y 18 16 14 12 > 10 8 6 4 0 0.5 1 Script> 1.5 1 2 X 2.5 3 3.5 Given a range (upper and lower limits) and increment, use the midpoint approximation as shown above to estimate the area under the curve: x² + 2x In (x) You can assume that the increment given will evenly divide the range. 4 1% Variables to be used 2% Inputs 3 % Xmin the minimum limit of the range 4% Xmax - the maximum limit of the range 5 % inc the increment for the numerical approximation Save C Reset My Solutions > 6 7 % Outputs 8% area - the final approximation of the area under the curve for the given range 9 10% Inputs 11% This generates the scalars, Xmin, Xmax, and inc, with random values which will be used to evaluate your code |12 Xmin=randi(10)+1 13 inc=randi(3) 14 Xmax=Xmin+inc×(randi(8)+2) 15 16 % Program 17% Start writing your program here MATLAB Documentation
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