The University of Science and Technology. And Linear Algebra.

 

MA 2071  Linear Algebra      D '03

 

Join the Quest for Maw in the Math Awareness Week contest!! Follow this

link to find out how to begin the hunt!!!!

 

 

All Project #2s due on Thursday, April 10 at the start of class. Please let me know well before then if you need help!!!

               ME Project #2  has rewording on Problem #6…

 

Instructional Staff

instructor:  John Goulet   Stratton 201 A    goulet@wpi.edu

                        office hours

                                    Monday  9:15-12, 1-3  ( 10:30-11  today 3/18)

                                    Tuesday 9:15-12, 12:30-2

                                    Thurs 9:15-12, 12:30-2

                                    Friday 9:30-12, 12:30-2        

                                    or by appointment

Sections:   (all conferences meet in Stratton 106 on Weds)

section D01 – 3:00   Joanna Begin         (jbegin@wpi.edu)

section D02 – 1:00   Jeff Simone            (jss328@wpi.edu)

section D03 – 12:00  Iavor Trifonov       (trifonov@wpi.edu)

section D04 – 11:00  Sidharth Rupani    (sidrup@wpi.edu)

section D05 – 8:00    Matt Black            (mblack@wpi.edu)

                         

Text:  Kolman, Linear Algebra with Applications ,7th ed

 

Grade:

quizzes (5)       35%   each Friday

projects           30%

final exam        25%             

homework       10%

 

5 point bonus for perfect attendance!

 

Bonus: the team with the highest quiz average does not have to take the final exam

Quizzes

 

            #1 – 3/14/03

      1. Gauss-Jordan elimination
      2. 3 types of solutions & Final Form
      3. assigning arbitrary variables
      4. no calculators

#2 – 3/21/03

1.      matrix arithmetic

                  notes from class 3/20 on matrix algebra rules

2.      vector form of solutions to systems

homogeneous, particular parts

1.      terminology (definitions):  “homogeneous, particular solutions”

 

#33/28/03

                  1.  matrix algebra

                  2.  inverses

                        under what conditions does a matrix have an inverse?

                        what relation does that have to solutions of Ax = b  ?  Ax = 0?

                  3.  determinants

                        compute, relate result to inverses

#4  4/4/03

1.     solution sets of homogeneous systems as vector spaces

      bases and dimension of

2.     vector spaces

                        showing a set is a vector space

                        finding counterexamples

                        you must know the definition of a vector space!

#5  4/11/03

        1. deciding if a set of vectors is a bases for Rn or not
        2. computing coordinates of a vector relative to a bases

      ( so be able to set up, solve  the problem  Pc = x )

        1. deciding if a basis is an orthogonal basis or not
        2. computing coefficients via dot products  (see notes from class on 4/8)

you must know the definition of a bases!

 

Groups 60,70 and 110 are tied for first place after 4 quizzes.  Groups 45 and 53 are

close behind!!!  Winner gets to skip the Final Exam!!

 

Homework

            assignments given daily at the beginning of class, by section

            see the following  file

           

Course  Philosophy

 

                follow this link for an overview of what this course is about

            a paper discussing the evolution of this course is at this link.

 

            Essentially, upon completion of the course, you will have worked on

                   Core Linear Algebra material

                        * learned basic definitions from linear algebra

                        * developed skills in linear algebra computations

                                    (solving linear systems, matrix arithmetic, use of linear transformations…)

                        * related computations to general linear algebra concepts (what a linear transformation is,

                                    how a basis is used,…)

                    Projects

                        * used linear algebra for applications within your major via projects

                        * worked in teams. Follow this link for group paper due Thursday 3/20

                        * presented project materials as teams which involves writing

 

Time Investment

            As with any 1/3 unit course, it is assumed that the total time spent per week, including class and

all activities, will be about 14 hours, on the average.  Aside from class, you will to a certain

extent need to work in parallel on both core linear algebra material  (homework and quiz preparation)

 and your projects.

 

Conferences

            Each Weds in conference, skill areas will be covered, in a cooperative format. That means that the

students in the conference will work on problems to try and get their computational skills in order. The

 PLAs managing the conferences will critique their work so that they are up to speed, so to speak,

on the skills covered.

 

            The specific skills covered in each conference may be found at this link.

 

 

Core Material  Covered:

Linear Systems

            types of problems

            types of solutions

                        arbitrary variables

            the Gauss-Jordan algorithm

           

Matrix Arithmetic and Algebra

            matrix arithmetic

            matrix algebra

            diagonal and symmetric matrices

            A = PDP-1 

            inverses and powers of matrices

            relation of matrices to solutions of systems – rank

            change of coordinates

Row vs Column Views of Solutions of Systems

                        Ax thought of as a linear combination of the columns of A 

Vector Spaces           

            basis

                        concept of building blocks

                        determining if a set is a basis or not

            coordinates and coordinate changes   x = Pc

                        how to build and use the P matrix for coordinate changes

            orthogonal basis

                        basis where all vectors in it are perpendicular to each other (0 dot product)

                        at the heart of Fourier analysis

                        key formula:   ci = xvi/vivi  

                        special case: orthonormal basis (all unit vectors)

real and abstract vector spaces

            “closure” requirements

            Rn

            planes and lines through the origin

            solutions to homogeneous systems

            solutions to homogeneous 2nd order differential equations

            sets of functions

            Determinants

                        Basic Properties

                        Relation to inverses, to solutions of systems, to rank

                        Useful Theorems

                                    Product Rule, Det(At) = Det(A) etc

                        Computing by hand:

                                    XXX rule, Cofactor Expansion

                        Cross Products

                        Geometric Interpretation

Linear Transformations

            definition

            Laplace and Fourier; derivatives and integrals

            matrix of

            application to rotations, reflections

            determined entirely by effect on basis for domain

            when is a linear transformation 1-1??

Diagonalization and the Principal Axis Theorem

            eigenvalues and eigenvectors – recognizing, computing

            when can a matrix be diagonalized?

            how do you diagonalize?

            applications:

            powers of matrices

                        behavior of dynamical systems

                        conic sections

Technology

                Adobe Acrobat Reader for .pdf files will be needed. Please install it if you don’t have it already.

                                go to the following  link to download

 

            Maple

                        this link has information on installing Maple over the college’s network as well as using

                        Maple to do linear algebra computations such as Gauss-Jordan, matrix arithmetic and

                        eigenvalue analysis.

 

                        This link goes to the Maple site at the University of Waterloo and has numerous sheets

                        with linear algebra applications.

 

            Matlab

                        This link is to a WPI site with 3 purposes:

        1. getting started with the Matlab software package
        2. common concepts (“bridges”) between linear algebra and signal analysis
        3. applications of signals and Matlab to sounds (voice, music)

Follow this link to see how Matlab solves linear algebra problems such as matrix

                        multiplication and eigenvalue/vector computations.

 

 Projects

A primary component of the WPI approach to education is the project. As all of you know,

you will participate in team projects at junior and senior level (the IQP and MQP, respectively).

These will require many things of you: working in a team, communicating orally and in writing,

planning, using technology and other resources, learning things you knew nothing about before,

and finally, providing a solution to a complex problem of society or in one’s major.

 

            (links not in place yet for IE….)

 

            Bio

 

            Civil Engineering

 

            Computer Science

 

            ECE

 

            Industrial Engineering

 

            Mathematics

 

            Mechanical Engineering   meeting Monday (4/7) with Matt – 5 pm, PLC (Daniels)

 

            Physics