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(Numerical Differentiation) Suppose we are given a function f(x) whose drivative is not known explicitly. We may, however, wish to still approximate the value of the derivative of f at a fixed point. In order to do this, we could use the so-called second- order centered difference formula given by S(r+h) – S(x - h) S'(1) = 2h Other approximations exist and are studied in numerical analysis (MAT 4020). diff_cdf Function: Input variables: • an anonymous function representing S • a scalar representing the location r where the derivative is desired • a scalar representing the value of h to be used in the approximation Output variables: • a scalar representing the approximate value of f'(x) computed using the above formula A possible sample case is: > df = diff_cdf(@(x) sin(x), 0, 0.1) df = 0.99833

(Numerical Differentiation) Suppose we are given a function f(x) whose drivative is not known explicitly. We may, however, wish to still approximate the value of the derivative of f at a fixed point. In order to do this, we could use the so-called second- order centered difference formula given by S(r+h) – S(x - h) S'(1) = 2h Other approximations exist and are studied in numerical analysis (MAT 4020). diff_cdf Function: Input variables: • an anonymous function representing S • a scalar representing the location r where the derivative is desired • a scalar representing the value of h to be used in the approximation Output variables: • a scalar representing the approximate value of f'(x) computed using the above formula A possible sample case is: > df = diff_cdf(@(x) sin(x), 0, 0.1) df = 0.99833

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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make a code , if you can uses mathlab

keep basic code no if or return 

(Numerical Differentiation) Suppose we are given a function f(x) whose drivative is not known explicitly. We may, however, wish to still approximate the value of the derivative of f at a fixed point. In order to do this, we could use the so-called second- order centered difference formula given by S(r+h) – S(x - h) S'(1) = 2h Other approximations exist and are studied in numerical analysis (MAT 4020). diff_cdf Function: Input variables: • an anonymous function representing S • a scalar representing the location r where the derivative is desired • a scalar representing the value of h to be used in the approximation Output variables: • a scalar representing the approximate value of f'(x) computed using the above formula A possible sample case is: > df = diff_cdf(@(x) sin(x), 0, 0.1) df = 0.99833
Transcribed Image Text:(Numerical Differentiation) Suppose we are given a function f(x) whose drivative is not known explicitly. We may, however, wish to still approximate the value of the derivative of f at a fixed point. In order to do this, we could use the so-called second- order centered difference formula given by S(r+h) – S(x - h) S'(1) = 2h Other approximations exist and are studied in numerical analysis (MAT 4020). diff_cdf Function: Input variables: • an anonymous function representing S • a scalar representing the location r where the derivative is desired • a scalar representing the value of h to be used in the approximation Output variables: • a scalar representing the approximate value of f'(x) computed using the above formula A possible sample case is: > df = diff_cdf(@(x) sin(x), 0, 0.1) df = 0.99833
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