Add to ORKGThe effectiveness of decomposing complex spectral contours into components using the least squares method is compared to that of a genetic algorithm with distortion of the input signal by low-frequency fractal noise. © Allerton Press, Inc., 2012
International audienceWe show that the Fourier transform of very complex spectra gives a sound measu...
In the paper we deal with the removal of a noise from a high-resolution stellar spectra. For this pu...
Two measures are commonly used to describe scale-invariant complexity in images: fractal dimension (...
The effectiveness of decomposing complex spectral contours into components using the least squares m...
© Published under licence by IOP Publishing Ltd. The approach based on the stochastic algorithm of p...
The problem of improving the resolution of composite spectra with statistically self-similar (fracta...
© Published under licence by IOP Publishing Ltd. An application of the artificial immune system meth...
The bee swarm algorithm is adapted for the solution of the problem of deconvolution of complex spect...
© 2016, Allerton Press, Inc.An approach based on stochastic particle swarm optimization is used for ...
Fractal dimension (D) is widely utilized in various fields to quantify the complexity of signals and...
Due to uncertainty in it, noise prevents exact prediction of the future from the past. Noise is gene...
Abstract: Based on the concept of Big Data Modeling, the errors in determining peak parameters of no...
Background: Chaos and random fractal theories are among the most important for fully characterizing ...
The article deals with the technology of estimating the frequency of harmonic components in the pres...
In the framework of the statistical regularization method new algorithms of solving inverse problems...
International audienceWe show that the Fourier transform of very complex spectra gives a sound measu...
In the paper we deal with the removal of a noise from a high-resolution stellar spectra. For this pu...
Two measures are commonly used to describe scale-invariant complexity in images: fractal dimension (...
The effectiveness of decomposing complex spectral contours into components using the least squares m...
© Published under licence by IOP Publishing Ltd. The approach based on the stochastic algorithm of p...
The problem of improving the resolution of composite spectra with statistically self-similar (fracta...
© Published under licence by IOP Publishing Ltd. An application of the artificial immune system meth...
The bee swarm algorithm is adapted for the solution of the problem of deconvolution of complex spect...
© 2016, Allerton Press, Inc.An approach based on stochastic particle swarm optimization is used for ...
Fractal dimension (D) is widely utilized in various fields to quantify the complexity of signals and...
Due to uncertainty in it, noise prevents exact prediction of the future from the past. Noise is gene...
Abstract: Based on the concept of Big Data Modeling, the errors in determining peak parameters of no...
Background: Chaos and random fractal theories are among the most important for fully characterizing ...
The article deals with the technology of estimating the frequency of harmonic components in the pres...
In the framework of the statistical regularization method new algorithms of solving inverse problems...
International audienceWe show that the Fourier transform of very complex spectra gives a sound measu...
In the paper we deal with the removal of a noise from a high-resolution stellar spectra. For this pu...
Two measures are commonly used to describe scale-invariant complexity in images: fractal dimension (...