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Linear Algebra - Welcome to the University of Delaware
Linear Algebra - Welcome to the University of Delaware

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Introduction to Linear Transformation

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... certificates. An alternative, less cheap, but exact method uses simultaneous diagonalization, which are applicable when d ≤ min(m, n). Applying these methods will often be successful when a rank-one basis exists, but fails if not. This tensor approach seems to have been overseen in the discrete opti ...
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Let u1,u2,... ,uk ∈ Rn, and let v1,v2,... ,vm ∈ span(u 1,u2,... ,uk).

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Complex 2 - D Vector Space Arithmetic

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Simple exponential estimate for the number of real zeros of

... The operator L G 2) is called irreducible, if the monodromy group of this operator is irreducible, i.e. the operators M^ have no common invariant nontrivial subspace. For Fuchsian operators (equations) an equivalent algebraic formulation can be given as follows: L is irreducible if and only if it ad ...
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... Definition 15. The span of the vectors v 1 , v 2 , . . . , v n is the set of all linear combinations of v 1 , v 2 , . . . , v n : it is written span{v1 , v 2 , . . . , v n }. In a vector space, all finite sums of the form λ1 v 1 + λ2 v 2 + · · · + λn v n are well-defined, i.e., have an unambiguous me ...
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on the complexity of computing determinants
on the complexity of computing determinants

... running time of the used algorithms. A classical methodology is to compute the results via Chinese remaindering. Then the standard analysis yields a number of fixed radix, i.e. bit operations for a given problem that is essentially (within polylogarithmic factors) bounded by the number of field oper ...
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Course Notes - Mathematics for Computer Graphics トップページ

... constrast, dual quaternion and axis-angle presentation are useful in rigid transformation (rotation and translation altogether). These mathematical concepts have become quite popular and have a success to some extent in our graphics community. In this section we therefore take a brief look at the or ...
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Eigenvalues and eigenvectors

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