While in [ 30] this technique was used ad hoc for accelerating RNA folding, it is possible to decouple the description of the fast matrix multiplication technique from the RNA folding algorithm, and present the algorithm of [ 30] in the same framework presented here.
The linear techniques have an advantage in that embedding can be performed by matrix multiplication; however, these techniques lack the representational ability of the nonlinear techniques [1, 5].
Nevertheless, we believe that the matrix multiplication-based techniques for improving the time complexity presented in this paper can also be incorporated to the algorithm of [ 9], however the details of this enhancement are beyond the scope of this paper.
Systolic arrays are being used for matrix operations and required specific processing algorithms, such as, transform techniques, matrix multiplication, convolution, and so forth, [21, 22].
The matrix multiplication was repeated multiple times until the spectrum matches the observed spectrum.
However, the complexity of the circuits needed for the support of the simulated CS technique would be extremely higher (matrix multiplication, digitization and resolution of the floating point values and measurements, optimization problem solving).
In the experiments with three applications (matrix multiplication, 2D FFT, and H.264/AVC encoding), compared with the conventional DSM, our techniques show performance improvement up to 37.89%.
This paper presents a simplification and a generalization of Valiant's technique, which speeds up a family of algorithms by incorporating fast matrix multiplication procedures.
In the original paper [ 29], this technique was applied to obtain an O log n) improvement factor for Boolean Matrix Multiplication.
