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Homework 2 | Numerical Analysis - Spring 2009 | MATH 435, Assignments of Mathematical Methods for Numerical Analysis and Optimization

Material Type: Assignment; Professor: Datta; Class: Numerical Analysis; Subject: MATHEMATICAL SCIENCES; University: Northern Illinois University; Term: Spring 2009;

Typology: Assignments

Pre 2010

Uploaded on 08/18/2009

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MATH 435
Spring 2009 Prof. B. Datta
Homework #2
Due: February 13, 2009
1. The polynomial P8(x) = x8+ 2x7+x6+ 2x5+ 5x3+ 7x2+ 5x+ 7 has a pair of
complex-conjugate zeros x=±i. Approximate them using Muller’s method. (Do
three iterations) Choose x0= 0, x1= 0.1, x2= 0.5.
2. The polynomial P6(x)=3x67x38x2+ 12x+ 3 = 0 has a double root at x=1.
Approximate this root first by using standard Newton’s method and then by two
modified Newton’s methods, starting x0=0.5.
Use Horner’s method to find the polynomial value and its derivative at each iteration.
Present your results in tabular form. (Do three iterations.)
3. Starting with x0= 0, and x1= 0.5, generate a set of approximations {x2, . . . , xk, xk+1 , . . .}
until |xk+1 xk|<0.0005 to find a zero of f(x) = tan(x)x, based on fixed point
iteration. Then compute {ˆxk}using Aitken’s acceleration scheme. Compare how con-
vergence is improved. Check if the convergence is improved by Aitken’s scheme if
Newton’s method is used in place of fixed-point iteration.
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MATH 435

Spring 2009 Prof. B. Datta Homework # Due: February 13, 2009

  1. The polynomial P 8 (x) = x^8 + 2x^7 + x^6 + 2x^5 + 5x^3 + 7x^2 + 5x + 7 has a pair of complex-conjugate zeros x = ±i. Approximate them using Muller’s method. (Do three iterations) Choose x 0 = 0, x 1 = 0. 1 , x 2 = 0.5.
  2. The polynomial P 6 (x) = 3x^6 − 7 x^3 − 8 x^2 + 12x + 3 = 0 has a double root at x = −1. Approximate this root first by using standard Newton’s method and then by two modified Newton’s methods, starting x 0 = − 0 .5. Use Horner’s method to find the polynomial value and its derivative at each iteration. Present your results in tabular form. (Do three iterations.)
  3. Starting with x 0 = 0, and x 1 = 0.5, generate a set of approximations {x 2 ,... , xk, xk+1,.. .} until |xk+1 − xk| < 0 .0005 to find a zero of f (x) = tan(x) − x, based on fixed point iteration. Then compute {xˆk} using Aitken’s acceleration scheme. Compare how con- vergence is improved. Check if the convergence is improved by Aitken’s scheme if Newton’s method is used in place of fixed-point iteration.