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Surprisingly, under mild conditions on (using the spark (mathematics), the mutual coherence or the restricted isometry property) and the level of sparsity in the solution, , the sparse representation problem can be shown to have a unique solution, and BP and MP are guaranteed to find it perfectly. [1] [2] [3]
Decomposition method is a generic term for solutions of various problems and design of algorithms in which the basic idea is to decompose the problem into subproblems. The term may specifically refer to: Decomposition method (constraint satisfaction) in constraint satisfaction
Top: The action of M, indicated by its effect on the unit disc D and the two canonical unit vectors e 1 and e 2. Left: The action of V ⁎, a rotation, on D, e 1, and e 2. Bottom: The action of Σ, a scaling by the singular values σ 1 horizontally and σ 2 vertically. Right: The action of U, another rotation.
In mathematics, a polynomial decomposition expresses a polynomial f as the functional composition of polynomials g and h, where g and h have degree greater than 1; it is an algebraic functional decomposition. Algorithms are known for decomposing univariate polynomials in polynomial time.
The commented Poisson problem does not have a solution for any functional boundary conditions f 1, f 2, g 1, g 2; however, given f 1, f 2 it is always possible to find boundary functions g 1 *, g 2 * so close to g 1, g 2 as desired (in the weak convergence meaning) for which the problem has solution. This property makes it possible to solve ...
For example, the equation (+) = has no real solution, because the square of a real number cannot be negative, but has the two nonreal complex solutions + and . Addition, subtraction and multiplication of complex numbers can be naturally defined by using the rule i 2 = − 1 {\displaystyle i^{2}=-1} along with the associative , commutative , and ...
Decomposition: This is a version of Schur decomposition where and only contain real numbers. One can always write A = V S V T {\displaystyle A=VSV^{\mathsf {T}}} where V is a real orthogonal matrix , V T {\displaystyle V^{\mathsf {T}}} is the transpose of V , and S is a block upper triangular matrix called the real Schur form .
In algebra, the partial fraction decomposition or partial fraction expansion of a rational fraction (that is, a fraction such that the numerator and the denominator are both polynomials) is an operation that consists of expressing the fraction as a sum of a polynomial (possibly zero) and one or several fractions with a simpler denominator.
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