Please
the
Theorem 4 from the section 1.4:
It reads
Let A be an mxn matrix. Then the following are logically equivalent. That is, for a
particular A, either all the following statements are true
or they are all false.
a. For each b in R m , the equation A
Lesson 4:
First read the definitions in the section 1.3 and then check if you can recall the
follwoing:
Vectors in R 2 :
Terminology:
A matrix with only one column is called a column vector or simply a vector.
We shall regard the two dimensional plane as
Lesson 3:
Please make sure that you are proficient with the following terminologies.
1. Leading entry
2. Echelon form
3. Reduced Echelon Form
If not, please read the lesson 2 and also the pages 14 and 15 of the text book to
review the above.
Now we are go
Lesson 2:
This lesson is mainly devoted to vocabulary which will be very important
to understand the upcoming ideas.
First recall from the lesson 1 that
The row operations on a matrix are
1. Interchanging any two rows
2. Multiplying a row by a non zero nu
Lesson 7:
In this lesson, we shall discuss how to describle the solutiuon set of a system
of linear equations.
First some terminologies:
If b0, we say that the system of linear equations Axb is homogeneous .
_
Example 1:
x 1 2x 2 x 3 x 4 0
x 1 x 2 x 3 4x
Greetings:
I am trying to keep these lessons as close to actual class room settings as
possible.
They do not intend to replace the text book actually they will involve the text
book.
An advantage of a distance learning course is that you may be able to go
Iniese Umah
MA 284
Prof Gavilanez
Search Engine
Introduction:
Mat-lab is an application package that uses Numerical methods and technique to solve arithmetic
and logical operations. The Numerical method greatly expands the type of problems one can
address
his routine
normalizes the matrix
Math 284
April 27, 2011
Name: Inese Umah
This worksheet contains a list of MATLAB commands that you may want/need to use for the take home
linear algebra exam, PART I. Note: I have included the commands, but not their mea
Preface
Here are my online notes for my Linear Algebra course that I teach here at Lamar University.
Despite the fact that these are my class notes they should be accessible to anyone wanting to
learn Linear Algebra or needing a refresher.
These notes do
clear all; close all; clc ;
%1), generating 10 columns and 3 row matirx
A = rand(3,10);
disp(A);
%2) determinig the cosine angle betweeb it and the vector
B = [1 2 3];
disp(B)
d
disp('The ten angles are:')
% %Iniese Umah
% Part 1, (writing M-file)
clear all; close all; clc ;
%1), generating a random matrix A with 10 columns and 3 row matirx
A = rand(3,10);
disp(A);
%2) determinig the cosine angle betweeb it and the vector
B = [1; 2; 3];
disp(B);
d
disp('The
%Iniese Umah
earch engine operation
close all; close all; clc;
A = rand(50,900); %represent 50 words and 900 articles
A = vertcat(A,A,A,A);
x = A(:,1);
syms Z Y integer
Y = 0;
% Z counting variable
% Y column count
% K determines the number of range of co
%Iniese Umah
clear all; close all; clc;
A = rand(50,900);
A = vertcat(A,A,A,A);
[P D Q] = svds(A,30);
B = P*D*transpose(Q);
x = A(:,1);
syms Z Y K integer
Y = 0;
for i = 1:length(B);
Z(i) = Y + i;
theta1(i) = (dot(B(:,i),x)/(sqrt(sum(B(:,i).^2)*sqrt(sum(x
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