meljun cortes numerical algorithm

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MELJUN CORTES Numerical Algorithm

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(c) 2009 Revathi Narasimhan All rights reserved

History of Numerical Algorithms

Reva Narasimhan

Kean University, Union, NJ

(c) 2009 Revathi Narasimhan All rights reserved

Overview

History Review of important people and

projects Examples of importance of

understanding numerical algorithms Role in teaching with technology

(c) 2009 Revathi Narasimhan All rights reserved

Introduction

What is numerical analysis, also referred to as scientific computing?

An integration of mathematical analysis, software,and large, complex problems in applications

Why is it important? Most equations cannot be solved by analytical

methods.

(c) 2009 Revathi Narasimhan All rights reserved

Beginnings…

Began with the 1947 paper by John von Neumann and Herman Goldstine, "Numerical Inverting of Matrices of High Order" (Bulletin of the AMS, Nov. 1947). It is one of the first papers to study rounding error and include discussion of what today is called scientific computing.  

(c) 2009 Revathi Narasimhan All rights reserved

Beginnings…

ENIAC was the first electronic digital computer. Funded by the U.S. Army to help with calculation of trajectories of ballistics (early 1940’s)

At that time, computer time was extremely expensive

(c) 2009 Revathi Narasimhan All rights reserved

Numerical Analysis Specialities

numerical linear algebra: used in digital imaging and compression

numerical methods for ordinary and partial differential equations: Aircraft and automobile design Computational finance Computational biology Weather forecasting

methods of approximation of functions: used in approximating curves in CAD/CAM design

(c) 2009 Revathi Narasimhan All rights reserved

Important People and Projects

James Wilkinson : round off error analysis and solving eigenvalue problems. (Late 50’s, Early 60’s)

Cooley-Tukey: FFT algorithm (1960’s) Peter Lax (Courant Institute) – numerical PDE’s EISPACK and LINPACK projects run by the

Argonne National Laboratory to produce high quality, tested and portable mathematical software during the early- to mid-1970s. These were linear algebra packages written

in FORTRAN

(c) 2009 Revathi Narasimhan All rights reserved

Important People and Projects

QUADPACK project : numerical integration package (mid 1970’s)

Bill Gear, Lawrence Shampine: Numerical ODE’s (1980’s)

Cleve Moler : founder of MATLAB; (late 1980’s)

Stephen Wolfram : founder of Mathematica (early 1990’s)

(c) 2009 Revathi Narasimhan All rights reserved

Math Software Packages

Many of the early software were incorporated in MATLAB, Maple and Mathematica

Sophisticated mathematical analysis can also be done by Excel – widely used in engineering and business

(c) 2009 Revathi Narasimhan All rights reserved

Numerical algorithms commonly in use

Simplex method for linear programming Splines in CAD/CAM design Matrix computations for digital imaging Digital animation (Toy Story, Shrek…) Numerical fluid dynamics for simulation of

blood flow Options pricing models in finance

(c) 2009 Revathi Narasimhan All rights reserved

Example: Digital Imaging

A picture can be represented as a m X n array, with each element of the array representing the color value at that point

Using the language of linear algebra, this array can be manipulated in many ways

Algorithm in numerical linear algebra play an important role in the manipulation of digital images

In addition to numerical linear algebra, statistics and signal processing tools are also used

(c) 2009 Revathi Narasimhan All rights reserved

Images in MATLAB

A=imread('spring_bulbs.jpg');

Name Size Bytes A 480x320x3 460800 Three dimensional array to

store RGB value

Grand total is 460800 elements using 460800 bytes

(c) 2009 Revathi Narasimhan All rights reserved

Read Image from Matrix

The following command displays the image stored in the matrix A: » imagesc(A)

Further refinements require image processing toolbox in MATLAB

(c) 2009 Revathi Narasimhan All rights reserved

Image processing in software

This Adobe web page shows how to use matrices in refining an image

(c) 2009 Revathi Narasimhan All rights reserved

Roundoff error and significant digits

Since machines can support only a finite number of digits, it is important to know the effect of rounding error

To understand rounding error, examine a simple problem

(c) 2009 Revathi Narasimhan All rights reserved

Example: Curve Fitting

Examine data in Example of population growth

(c) 2009 Revathi Narasimhan All rights reserved

Teaching with Technology

Nonlinear equation solvers: use of Newton’s method

Numerical Integration Numerical solution of ODE’s

(c) 2009 Revathi Narasimhan All rights reserved

Newton’s Method

(c) 2009 Revathi Narasimhan All rights reserved

Role of Mathematical analysis

How does the behavior of the function affect the root that you find?

What happens if your initial guess is near a local maximum or minimum?

How many roots are there anyway? Thus, proper use of technology

requires a higher level of conceptual understanding

(c) 2009 Revathi Narasimhan All rights reserved

Root finding in the TI-84

Left and right bound – find the interval where function changes sign; use bisection method

Use of guess – employing variation of Newton’s Method

(c) 2009 Revathi Narasimhan All rights reserved

Goal Seek in Excel

This is really a nonlinear equation solver using an iterative method

In the 1970’s and 1980’s, numerical computations were done on mainframes

Now, a lot of quantitative analysis takes place on the desktop PC, using Excel

(c) 2009 Revathi Narasimhan All rights reserved

Role of mathematical analysis

What is the implication for mathematics education?

Examine a simple polynomial equation:

013 xx

(c) 2009 Revathi Narasimhan All rights reserved

Analysis …

Can the root be found by elementary methods?

If found numerically, how do we know there is only one real root?

(c) 2009 Revathi Narasimhan All rights reserved

Implication for Technology in Education

Important for students to be familiar with effects of roundoff error

Spreadsheets are used in analysis of large amounts of data and is a tool for all commercial and governmental decision-makers.

A robust quantitative curriculum: numerical methods, introduction to computer simulation, and statistics.

“Quantitative arguments are underpinning successful business and political decisions. Students of commerce and government must become equally skilled consumers of quantitative information.” (Deborah Hughes-Hallett, 2000)

(c) 2009 Revathi Narasimhan All rights reserved

Summary

Wide use of numerical algorithms brings about new ideas in teaching mathematics

Quantitative literacy involves knowing how to use technology such as a spreadsheet to analyze a problem

Conceptual understanding is a necessity for proper use of technology

(c) 2009 Revathi Narasimhan All rights reserved

Contact Information

rnarasim@kean.edu http://www.mymathspace.net

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