@article{,
author={Kocsor, Andr{\'a}s and T{\'o}th, L{\'a}szl{\'o} and B{\'a}lint Imre},
title={On the Optimal Parameters of a Sinusoidal Representation of Signals},
abstract={In the spectral analysis of digital signals, one of the most useful parametric
models is the representation by a sum of phase-shifted sinusoids in form
of , where An , , and are the component's amplitude, frequency and phase,
respectively. This model generally fits well speech and most musical signals
due to the shape of the representation functions. If using all of the above
parameters, a quite difficult optimization problem arises. The applied
methods are generally based on eigenvalue decomposition [3]. However this
procedure is computationally expensive and works only if the sinusoids
and the residual signal are statistically uncorrelated. To speed up the
representation process also rather ad hoc methods occur [4]. The presented
algorithm applies the newly established Homogeneous Sinus Representation
Function (HSRF) to find the best representing subspace of fixed dimension
N by a BFGS optimization. The optimum parameters ensure the mean square
error of approximation to be below a preset threshold. },
journal={Acta Cybernetica},
volume={14},
year={1999},
pages={315-330},
number={2}
}