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The new solution is based on polynomial matrix calculus, mainly the so-called left S-inverse of the polynomial matrix.
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Both designed methods are based on polynomial approach.
PReach (Gabr et al., 2013) computes the exact reachability probability based on polynomial multiplication.
On the other hand, in the approach based on the polynomial matrix calculus [12 14], the aforementioned dysfunction is eliminated by using the PSVD (polynomial SVD) [15 17].
It is important that the proposed approach to perfect reconstruction of signal is based on the polynomial matrix calculus.
What is important is that the solution based on the polynomial matrix calculus (along with non-zero degrees of freedom, i.e., at (mathbf {underline {M}}left (q^{-1}right)neq mathbf 0)), is a new approach so far unknown in the field of the modern signal reconstruction.
All interpolation theory is based on polynomials.
It has been studied extensively and a number of approaches, mostly based on polynomials and piecewise polynomials, have been employed.
We introduce a novel, fast and scalable method to compute the reachability profile of large networks, based on polynomials and polynomial collapsing operators.
In this paper a method for computing hyperbolic matrix functions based on Hermite matrix polynomial expansions is outlined.
We start our optimization task in the Matlab environment with the degrees of freedom included in the parameter matrix; a more general case is based on the matrix polynomial.
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