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File: Matrix Pdf 174396 | Cfcs L10
properties of matrices transpose and trace inner and outer product computational foundations of cognitive science lecture 10 algebraic properties of matrices transpose inner and outer product frank keller school of ...

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                                         Properties of Matrices
                                          Transpose and Trace
                                      Inner and Outer Product
               Computational Foundations of Cognitive Science
               Lecture 10: Algebraic Properties of Matrices; Transpose; Inner
                                                  and Outer Product
                                                        Frank Keller
                                                     School of Informatics
                                                   University of Edinburgh
                                                   keller@inf.ed.ac.uk
                                                   February 23, 2010
                                                   Frank Keller      Computational Foundations of Cognitive Science            1
                                         Properties of Matrices
                                          Transpose and Trace
                                      Inner and Outer Product
           1 Properties of Matrices
                   Addition and Scalar Multiplication
                   Matrix Multiplication
                   Zero and Identity Matrix
                   Mid-lecture Problem
           2 Transpose and Trace
                   Definition
                   Properties
           3 Inner and Outer Product
           Reading: Anton and Busby, Ch. 3.2
                                                   Frank Keller      Computational Foundations of Cognitive Science            2
                                         Properties of Matrices      Addition and Scalar Multiplication
                                          Transpose and Trace        Matrix Multiplication
                                      Inner and Outer Product        Zero and Identity Matrix
                                                                     Mid-lecture Problem
     Addition and Scalar Multiplication
           Matrix addition and scalar multiplication obey the laws familiar
           from the arithmetic with real numbers.
           Theorem: Properties of Addition and Scalar Multiplication
           If a and b are scalars, and if the sizes of the matrices A, B, and C
           are such that the operations can be performed, then:
                   A+B=B+A(cummutativelaw for addition)
                   A+(B+C)=(A+B)+C (associative law for addition)
                   (ab)A = a(bA)
                   (a +b)A = aA+bA
                   (a −b)A = aA−bA
                   a(A+B)=aA+aB
                   a(A−B)=aA−aB
                                                   Frank Keller      Computational Foundations of Cognitive Science            3
                                         Properties of Matrices      Addition and Scalar Multiplication
                                          Transpose and Trace        Matrix Multiplication
                                      Inner and Outer Product        Zero and Identity Matrix
                                                                     Mid-lecture Problem
     Matrix Multiplication
           However, matrix multiplication is not cummutative, i.e., in general
           AB 6= BA. There are three possible reasons for this:
                   AB is defined, but BA is not (e.g., A is 2 × 3, B is 3 × 4);
                   AB and BA are both defined, but differ in size (e.g., A is
                   2×3, B is 3×2);
                   AB and BA are both defined and of the same size, but they
                   are different.
           Example
                                                                   
           Assume A = −1 0                          B = 1 2 then
                                    2      3                  3 0
                                                                
           AB = −1 −2                       BA= 3 6
                        11        4                      −3 0
                                                   Frank Keller      Computational Foundations of Cognitive Science            4
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...Properties of matrices transpose and trace inner outer product computational foundations cognitive science lecture algebraic frank keller school informatics university edinburgh inf ed ac uk february addition scalar multiplication matrix zero identity mid problem denition reading anton busby ch obey the laws familiar from arithmetic with real numbers theorem if a b are scalars sizes c such that operations can be performed then cummutativelaw for associative law ab ba aa however is not cummutative i e in general there three possible reasons this dened but g both dier size same they dierent example assume...

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