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MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms , creation of user interfaces , and interfacing with programs written in other languages.
Consequently, if all singular values of a square matrix are non-degenerate and non-zero, then its singular value decomposition is unique, up to multiplication of a column of by a unit-phase factor and simultaneous multiplication of the corresponding column of by the same unit-phase factor.
Includes Matlab Functions for calculating a homography and the fundamental matrix (computer vision). GIMP Tutorial – using the Perspective Tool by Billy Kerr on YouTube. Shows how to do a perspective transform using GIMP. Allan Jepson (2010) Planar Homographies from Department of Computer Science, University of Toronto. Includes 2D homography ...
Given an input matrix and a desired low rank , the randomized LU returns permutation matrices , and lower/upper trapezoidal matrices , of size and respectively, such that with high probability ‖ ‖ +, where is a constant that depends on the parameters of the algorithm and + is the (+)-th singular value of the input matrix .
Parallel analysis is regarded as one of the more accurate methods for determining the number of factors or components to retain. In particular, unlike early approaches to dimensionality estimation (such as examining scree plots), paralell analysis has the virtue of an objective decision criterion. [3]
Every finite-dimensional matrix has a rank decomposition: Let be an matrix whose column rank is . Therefore, there are r {\textstyle r} linearly independent columns in A {\textstyle A} ; equivalently, the dimension of the column space of A {\textstyle A} is r {\textstyle r} .
The biadjacency matrix of a simple, undirected bipartite graph is a (0, 1)-matrix, and any (0, 1)-matrix arises in this way. The prime factors of a list of m square-free, n-smooth numbers can be described as an m × π(n) (0, 1)-matrix, where π is the prime-counting function, and a ij is 1 if and only if the jth prime divides the ith number.
A square matrix is called a projection matrix if it is equal to its square, i.e. if =. [2]: p. 38 A square matrix is called an orthogonal projection matrix if = = for a real matrix, and respectively = = for a complex matrix, where denotes the transpose of and denotes the adjoint or Hermitian transpose of .