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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.
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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.
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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
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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
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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
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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)
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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
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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
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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
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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
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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
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Image processing in software
This Adobe web page shows how to use matrices in refining an image
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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
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Example: Curve Fitting
Examine data in Example of population growth
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Teaching with Technology
Nonlinear equation solvers: use of Newton’s method
Numerical Integration Numerical solution of ODE’s
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Newton’s Method
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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
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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
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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
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Role of mathematical analysis
What is the implication for mathematics education?
Examine a simple polynomial equation:
013 xx
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Analysis …
Can the root be found by elementary methods?
If found numerically, how do we know there is only one real root?
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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)
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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
[email protected] http://www.mymathspace.net
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