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The explicit polynomial that we consider is the iterated matrix multiplication polynomial of n generic matrices of size n×n.
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The polynomial matrix multiplication of a p × q matrix A z) and a q × t matrix B z) is defined as C ( z ) = A ( z ) B ( z ) c ij ( z ) = ∑ k = 1 q a ik ( z ) b kj ( z ).
Numerous cryptographic protocols and scientific computations are based on linear algebra, which can be reduced to some core problems, such as matrix multiplication, determinant and the characteristic polynomial of a matrix.
Finally, left matrix multiplication of both sides by the polynomial basis matrix given in Equation (30) results in the time domain reconstructed signal y ̂, i.e. y ̂ = P · G = P · W † · D · y.
The matrix multiplication was repeated multiple times until the spectrum matches the observed spectrum.
However, the polynomial method needs to calculate the high order matrix multiplication, therefore, it can not be implemented easily.
Conversion from the polynomial to Fourier coefficients is performed through simple matrix multiplication.
Projective transformations, which are invertible linear changes of homogeneous coordinates, are given by matrix multiplication.
sparse dense matrix multiplication.
Quaternion multiplication and matrix multiplication is also noncommutative.
Computational complexity of matrix inversion with Gaussian elimination is polynomial with O(n3), yet it can be as low as O(n2 log(n)) theoretically, which is the lower bound on matrix multiplication.
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