Linear Algebra Review By Tim K. Marks UCSD Borrows heavily from: Jana Kosecka
[email protected] http://cs.gmu.edu/~kosecka/cs682.html Virginia de Sa Cogsci 108F Linear Algebra review UCSD Vectors The length of x, a.k.a. the norm or 2-norm of x, is 2 2 2 x = x1 + x2 +L+ xn e.g., x = 32 + 22 + 52 = 38 ! ! 1 Good Review Materials http://www.imageprocessingbook.com/DIP2E/dip2e_downloads/review_material_downloads.htm (Gonzales & Woods review materials) Chapt. 1: Linear Algebra Review Chapt. 2: Probability, Random Variables, Random Vectors Online vector addition demo: http://www.pa.uky.edu/~phy211/VecArith/index.html 2 Vector Addition u+v v u Vector Subtraction u-v u v 3 Example (on board) Inner product (dot product) of two vectors # 6 & "4 % % ( $ ' a = % 2 ( b = $1 ' $%" 3'( #$5 &' a" b = aT b ! ! #4 & % ( = [6 2 "3] %1 ( ! $%5 '( = 6" 4 + 2"1+ (#3)" 5 =11 ! ! ! 4 Inner (dot) Product The inner product is a SCALAR. v α u 5 Transpose of a Matrix Transpose: Examples: If , we say A is symmetric. Example of symmetric matrix 6 7 8 9 Matrix Product Product: A and B must have compatible dimensions In Matlab: >> A*B Examples: Matrix Multiplication is not commutative: 10 Matrix Sum Sum: A and B must have the same dimensions Example: Determinant of a Matrix Determinant: A must be square Example: 11 Determinant in Matlab Inverse of a Matrix If A is a square matrix, the inverse of A, called A-1, satisfies AA-1 = I and A-1A = I, Where I, the identity matrix, is a diagonal matrix with all 1’s on the diagonal.