1. تهیه کننده : نرگس مرعشی استاد راهنما : جناب آقای دکتر جمشید شنبه زاده

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6.  Linear Independence  Rank of a Matrix  Matrix Norm  Singular Value Decomposition  Vector Cross Product to Matrix Multiplication  RANSAC 6

7.  A finite subset of n vectors is linearly dependent if and only if there exists a set of n scalars a1,a2,…,an,not all zero a 1 v 1 +a 2 v 2 +…+a n v n =0 7

8.  The column of a matrix A is the maximum number of linearly independent column vectors of A  The row rank of a matrix A is the maximum number of linearly independent row vectors of A  The column rank of A is the dimension of the column space of A  The row rank of A is the dimension of the row space of A 8

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10.  L1 matrix norm is maximum of absolute column sum 10

11. 11 Y=mx+c

12.  Least squares Fit(over constraint)  RANSAC(constraint)  Hough Transform(under constraint) 12

13. 13 y=mx+c=f(x,m,c) Minimize E=∑ i [y i -f(x i,m,c)] 2

14. 14 y=mx+c y 1 =mx 1 +c y 2 =mx 2 +c. y n =mx n +c A T B=A T AD (A T A) -1 A T B=(A T A) -1 (A T A)D D=(A T A) -1 A T B

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18. (AB) T =B T A T 18 1 2 3 5 4

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