Florida Institute of Technology

Instructor: Debasis Mitra

The Syllabus

Catalog Description: None at the moment! This is a Special Topic course for now. However, ...

Utilizing hands on approach in coding scientific and mathematical algorithms this course develops students programming skills. Sample topics are linear algebra, inter-extrapolation, data modeling, classification, inverse theory, etc.

Text book is "Numerical Recipes 3rd Edition: The Art of Scientific Computing," by William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery, Cambridge University Press, ISBN 0-521-75033-4.

Site at amazon, and

its site ,
also here.

Resources:

A linear algebra basics book page

A Cornell SciComp Class page

C++ Linear Algebra codes:

http://math.nist.gov/tnt/

http://www.alglib.net/

Some math encyclopedia-type resources:

http://rkb.home.cern.ch/rkb/titleA.html

http://planetmath.org/

A free text-book from Mathworks .

On SVD:

A copy-rtd easy tutorial for sqr matrix-svd algorithm.

data_driven_markov_chain_monte_carlo.ppt

painless-conjugate-gradient, from Stanford

RidderMethod paper

FlorentSegonneTutorialTopoMedImg07itcmiss.pdf

cardoso11_longitudinal_cortical_thickness_MICCAI.pdf

TopoSurface Rep-KovalevskyOrig1999.pdf

Khalimski grid ref

A C++ resource: from IBM?

A resource on presentation styles.

++++++++++ Spring 2017 +++++++++++++++++++++++

CRF 401, TR 6:30-7:45pm, CSE 5400/4510

Plan/activities for the semester - is being continuously updated!

++++++++++ Spring 2014 +++++++++++++++++++++++

Class: Crawford 403 Mondays-Wednesdays 8-9:15pm.

Plan/activities for the semester - is being continuously updated!

Dr. Allen's lectures on numerical precision and Gauss-Jordan basics.

======= Spring 2013 ================

Class: Crawford 403 Wednesdays 8-10pm.

Plan/activities for the semester - is being continuously updated!

Syllabus for Spr13:

Ch 2 Linear Alg., Ch 3 Interpolation, Ch 6 Spl. Functions, Ch 9 Roots of Equation, Ch 10 Optimzation, Ch 13 Spectral Analysis, and Ch 10 Inverse theory (7 chapters, ~15 weeks)

Before preparing the lecture/demo you may like to look at
my notes

Kim's Gauss-Jorddan elimination Ch2 talk

Jessie's LU decomposition Ch 2 talk

Shi and Bo's SVD and Conjugate Gradient Ch 2 talks

Yunfei and Hui's Plynomial Interpolation Ch 3
and, Multi-dimensional Interpolation Ch 3.6 presentations

Mike and Christian's Rational & Barycentric Interpolation Ch 3 talk

Kim & Jessie's Radial-basis Function interpolation Ch3 talk

Kim, Jessie & Christian's Newton-Raphson Ch9 1D root finding, talk

Mike and Vallerie Optimization Ch 10 talk

Yunfei and Hui's Optimization on 1D Ch10.3-4 presentation

Shi and Bo on nD Powell Ch10.7

Mike and Vallerie Convolution using FFT Ch 13.?, Convolution using FFT Ch 13.?, Wavelet basics Ch 13.?, Wavelet transform Ch 13.?, and more on use of Wavelet transform Ch 13.10.6-8 presentations.

Shi and Bo's slides on Linear eq solving with Wavelet Ch13.10.7

===========================

*Spring 2012:*

Class: Crawford 403 Wednesdays 8-10pm.

Plan/activities for the semester - is being continuously updated!

Raw numerical-simulation 3D image data:

(original: my Projects\Lbnl\MotnCorrc\RossPhantomData directory)
download

Width=128, Height=128, Depth ("Number of Images")=90, but you can give any larger number on ImageJ

Image type=32-bit Real, Little Endian Byte order(Intel format)

Both groups: start with down sampled image, 128x128x90 is too large now!

'/' command gives orthogonal view, ImageJ also has 3D viewer plugin. Enjoy!

===========================

*Spring 2011:*

Class: Crawford 403 Wednesdays 8-10pm.

UG CSE4510-E11 students: please come to the above class, and let me know that you are UG student.

The course have mostly student presentations and discussion, along with coding & projects.
We go over some chapters from the text for basic knowledge on the mathematical computing area, and then expect to code them.
We do explore some tools in the area.

Plan/activities for the semester - is being continuously updated!

Presentations:

LUP module

SVD

Quadrature

Grid N, Scattered Data, Laplace

Optimization-final

Linear Programming

LP-Interior-Point

Modeling Data Intro

Ch15- Data Modeling

Ch16- Expectation Maximization

Projects:

Digital enlargement preserving information, by Nawar Kabbani and Gregory Beckham: Report

Detection of traffic signals from a moving car, by Daniel Eiland and Mahmoud Abdallah: Presentation, Report

Edge detection by MCMC algorithm with Gibbs Sampling, by Michael Sedvy: Report

------------------------------------

*Materials are copyrighted to me (year 2010).*
*E-mail:
dmitra at fit dt edu*