New to MATLAB? Get Help Approximating a Root with Newton-Raphson

In summary, the code approximation p0 is calculated using Newton-Raphson method with the given initial approximation p0, tolerance delta, and maximum number of iterations max1. If the error estimate err<delta, the error relerr<delta, or the function value y is within the given function range epsilon, then the loop terminates and p0 is set to p1. Otherwise, p1 is set to p0 and the loop continues.
  • #1
Faux Carnival
12
0
Hello everyone, I am fairly new to MATLAB. I have to approximate a root of a given function with Newton-Raphson method.

I have a code that looks like this: (Newton.m)

Code:
function [p0,err,k,y] = Newton(f,df,p0,delta,epsilon,max1)

%Input     - f is the object function 
%            - df is the derivative of f 
%            - p0 is the initial approximation to a zero of f
%	         - delta is the tolerance for p0
%	         - epsilon is the tolerance for the function values y
%	         - max1 is the maximum number of iterations
%Output - p0 is the Newton-Raphson approximation to the zero
%	         - err is the error estimate for p0
%	         - k is the number of iterations
%	         - y is the function value f(p0)

%If f and df are defined as M-file functions use the @ notation
% call [p0,err,k,y]=Newton(@f,@df,p0,delta,epsilon,max1).
%If f and df are defined as anonymous functions use the
% call  [p0,err,k,y]=Newton(f,df,p0,delta,epsilon,max1).



%  NUMERICAL METHODS: Matlab Programs
% (c) 2004 by John H. Mathews and Kurtis D. Fink
%  Complementary Software to accompany the textbook:
%  NUMERICAL METHODS: Using Matlab, Fourth Edition
%  ISBN: 0-13-065248-2
%  Prentice-Hall Pub. Inc.
%  One Lake Street
%  Upper Saddle River, NJ 07458

for k=1:max1	
	p1=p0-f(p0)/df(p0);	
	err=abs(p1-p0);
	relerr=2*err/(abs(p1)+delta);
	p0=p1;
	y=f(p0);
	if (err<delta)|(relerr<delta)|(abs(y)<epsilon),break,end
end

What do I do now? I really need some help here. Do I need to define f and df first? And how?

Thanks.
 
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  • #2

Related to New to MATLAB? Get Help Approximating a Root with Newton-Raphson

1. What is MATLAB?

MATLAB is a high-level programming language and interactive environment commonly used in scientific and engineering applications. It allows users to perform complex mathematical computations and data analysis.

2. What is the Newton-Raphson method?

The Newton-Raphson method is an iterative numerical algorithm used to approximate the roots of a function. It involves using the derivative of the function to refine the initial guess and converge to a more accurate solution.

3. How do I use the Newton-Raphson method in MATLAB?

To use the Newton-Raphson method in MATLAB, you can use the built-in function 'fzero' or write your own algorithm using a loop that updates the initial guess using the function and its derivative. The algorithm should continue until the desired level of accuracy is achieved.

4. What are the advantages of using the Newton-Raphson method in MATLAB?

The Newton-Raphson method in MATLAB offers several advantages, such as its ability to handle complex functions and its fast convergence to a solution. It also allows for easy implementation and customization for different functions.

5. Are there any limitations to using the Newton-Raphson method in MATLAB?

Like any numerical algorithm, the Newton-Raphson method in MATLAB may encounter limitations, such as divergence if the initial guess is too far from the actual root or if the function has multiple roots. It is important to choose a suitable initial guess and ensure the function has a single root within the desired range.

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