Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add more filters











Database
Language
Publication year range
1.
Nonlinear Biomed Phys ; 5(1): 7, 2011 Sep 05.
Article in English | MEDLINE | ID: mdl-21892959

ABSTRACT

We propose several models applicable to both selection and election processes when each selecting or electing subject has access to different information about the objects to choose from. We wrote special software to simulate these processes. We consider both the cases when the environment is neutral (natural process) as well as when the environment is involved (controlled process).

2.
Nonlinear Biomed Phys ; 5: 3, 2011 Jun 22.
Article in English | MEDLINE | ID: mdl-21696574

ABSTRACT

BACKGROUND: Analysis of signals by means of symbolic methods consists in calculating a measure of signal complexity, for example informational entropy or Lempel-Ziv algorithmic complexity. For construction of these entropic measures one uses distributions of symbols representing the analyzed signal. RESULTS: We introduce a new signal characteristic named sequential spectrum that is suitable for analysis of the wide group of signals, including biosignals.The paper contains a brief review of analyses of artificial signals showing features similar to those of biosignals. An example of using sequential spectrum for analyzing EEG signals registered during different stages of sleep is also presented. CONCLUSIONS: Sequential spectrum is an effective tool for general description of nonstationary signals and it its advantage over Fourier spectrum. Sequential spectrum enables assessment of pathological changes in EEG-signals recorded in persons with epilepsy.

3.
Acta Neurobiol Exp (Wars) ; 62(4): 277-81, 2002.
Article in English | MEDLINE | ID: mdl-12659294

ABSTRACT

Spontaneous EEG of 21 healthy human subjects obtained by standard procedure of recording is analysed using non-linear prediction methods to check whether the signals were generated by a non-linear dynamics process or by a linear stochastic process. The test for non-linearity is performed by surrogate data method with non-linear prediction error as the test statistic. The null hypothesis that EEG signal (in rest, with eyes closed) is generated by linear stochastic process can be rejected in 17 cases (5%) out of the 336 (21 subjects, 16 channels) studied epochs. However, most of these rejections concern 3 subjects. The 88% of rejections of the null hypothesis concern frontal channels. The null hypothesis is not rejected for epochs recorded with eyes open and during photostimulation.


Subject(s)
Electroencephalography , Nonlinear Dynamics , Algorithms , Humans
SELECTION OF CITATIONS
SEARCH DETAIL