1.3 Vector Equations.

Slides:



Advertisements
Similar presentations
Linear Equations in Linear Algebra
Advertisements

Vector Spaces & Subspaces Kristi Schmit. Definitions A subset W of vector space V is called a subspace of V iff a.The zero vector of V is in W. b.W is.
ICS 6N Computational Linear Algebra
Vectors and Vector Equations (9/14/05) A vector (for us, for now) is a list of real numbers, usually written vertically as a column. Geometrically, it’s.
Matrices. Special Matrices Matrix Addition and Subtraction Example.
Matrix Operations. Matrix Notation Example Equality of Matrices.
Linear Equations in Linear Algebra
Little Linear Algebra Contents: Linear vector spaces Matrices Special Matrices Matrix & vector Norms.
4 4.2 © 2012 Pearson Education, Inc. Vector Spaces NULL SPACES, COLUMN SPACES, AND LINEAR TRANSFORMATIONS.
Section 4.1 Vectors in ℝ n. ℝ n Vectors Vector addition Scalar multiplication.
A matrix equation has the same solution set as the vector equation which has the same solution set as the linear system whose augmented matrix is Therefore:
Chapter 3 Vector Spaces. The operations of addition and scalar multiplication are used in many contexts in mathematics. Regardless of the context, however,
1 1.3 © 2012 Pearson Education, Inc. Linear Equations in Linear Algebra VECTOR EQUATIONS.
10.4 Matrix Algebra 1.Matrix Notation 2.Sum/Difference of 2 matrices 3.Scalar multiple 4.Product of 2 matrices 5.Identity Matrix 6.Inverse of a matrix.
Algebra 3: Section 5.5 Objectives of this Section Find the Sum and Difference of Two Matrices Find Scalar Multiples of a Matrix Find the Product of Two.
Section 2.3 Properties of Solution Sets
VECTORS (Ch. 12) Vectors in the plane Definition: A vector v in the Cartesian plane is an ordered pair of real numbers:  a,b . We write v =  a,b  and.
Copyright © Cengage Learning. All rights reserved. 7 Linear Systems and Matrices.
Meeting 18 Matrix Operations. Matrix If A is an m x n matrix - that is, a matrix with m rows and n columns – then the scalar entry in the i th row and.
Matrices and Systems of Equations
Sec 4.1 Matrices.
Copyright © Cengage Learning. All rights reserved. 2 SYSTEMS OF LINEAR EQUATIONS AND MATRICES.
Algebra Matrix Operations. Definition Matrix-A rectangular arrangement of numbers in rows and columns Dimensions- number of rows then columns Entries-
1.7 Linear Independence. in R n is said to be linearly independent if has only the trivial solution. in R n is said to be linearly dependent if there.
Introduction to Financial Modeling MGT 4850 Spring 2008 University of Lethbridge.
4 4.1 © 2016 Pearson Education, Ltd. Vector Spaces VECTOR SPACES AND SUBSPACES.
Chapter 4 Vector Spaces Linear Algebra. Ch04_2 Definition 1: ……………………………………………………………………. The elements in R n called …………. 4.1 The vector Space R n Addition.
Chapter 5 Chapter Content 1. Real Vector Spaces 2. Subspaces 3. Linear Independence 4. Basis and Dimension 5. Row Space, Column Space, and Nullspace 6.
The Matrix Equation A x = b (9/16/05) Definition. If A is an m  n matrix with columns a 1, a 2,…, a n and x is a vector in R n, then the product of A.
13.3 Product of a Scalar and a Matrix.  In matrix algebra, a real number is often called a.  To multiply a matrix by a scalar, you multiply each entry.
1 1.3 © 2016 Pearson Education, Ltd. Linear Equations in Linear Algebra VECTOR EQUATIONS.
2.1 Matrix Operations 2. Matrix Algebra. j -th column i -th row Diagonal entries Diagonal matrix : a square matrix whose nondiagonal entries are zero.
Copyright © Cengage Learning. All rights reserved. 7 Matrices and Determinants.
Matrices.
REVIEW Linear Combinations Given vectors and given scalars
1.4 The Matrix Equation Ax = b
MTH108 Business Math I Lecture 20.
Matrix Algebra MATRIX OPERATIONS © 2012 Pearson Education, Inc.
Linear Algebra review (optional)
CS479/679 Pattern Recognition Dr. George Bebis
Linear Equations in Linear Algebra
Chapter 1 Linear Equations and Vectors
Eigenvalues and Eigenvectors
Matrix Algebra MATRIX OPERATIONS © 2012 Pearson Education, Inc.
VECTOR SPACES AND SUBSPACES
Row Space, Column Space, and Nullspace
Section 7.4 Matrix Algebra.
7.3 Matrices.
Vectors, Linear Combinations and Linear Independence
Linear Algebra Lecture 22.
VECTOR SPACES AND SUBSPACES
Linear Equations in Linear Algebra
Linear Equations in Linear Algebra
2. Matrix Algebra 2.1 Matrix Operations.
4.6: Rank.
4.1 Matrices – Basic Operations
Linear Algebra Chapter 4 Vector Spaces.
Matrices and Matrix Operations
Linear Algebra Lecture 21.
Properties of Solution Sets
Linear Algebra Lecture 5.
Linear Algebra Lecture 24.
Linear Algebra Lecture 20.
Linear Algebra review (optional)
Vector Spaces, Subspaces
ABASAHEB KAKADE ARTS COLLEGE BODHEGAON
Matrix Algebra MATRIX OPERATIONS © 2012 Pearson Education, Inc.
NULL SPACES, COLUMN SPACES, AND LINEAR TRANSFORMATIONS
Eigenvalues and Eigenvectors
VECTOR SPACES AND SUBSPACES
Presentation transcript:

1.3 Vector Equations

Geometric Interpretation? Vectors in R2 : 1-column matrices or ordered pairs of real numbers Example: Given and , find Geometric Interpretation?

Vectors in R3 : column matrices or points in three-dimensional space Vectors in Rn : column matrices

Two vectors are equal if and only if their corresponding entries are equal. The vector (where c is a real number) is a scalar multiple of .

Algebraic Properties of

Linear Combinations Given vectors and given scalars is a linear combination of with weights Example:

Example: Determine whether w can be generated as a linear Combination of v and v , where , , and .

A vector equation has the same solution set as the linear system whose augmented matrix is can be generated by a linear combination of vectors in if and only if the following linear system is consistent:

Definition If , then the set of all linear combinations of is denoted by Span and is called the subset of spanned by

Geometric Description of Span: