WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
Browse
3 results
Search Results
Article Citation - WoS: 3Correntropy Function for Fundamental Frequency Determination of Musical Instrument Samples(Elsevier Ltd., 2011) Özbek, Mehmet Erdal; Savacı, Ferit Acar; Savacı, Ferit Acar; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyFundamental frequency or pitch determination is one of the main issues in the transcription of music. In this paper, we determined the fundamental frequencies of isolated musical instrument samples by computing the correntropy functions. As the correntropy function depends on kernel methods, we demonstrated its performance using various kernel sizes. We presented the better resolution of the correntropy function than the conventional and the summary autocorrelation functions by calculating the full-width-at-half-maximum of the peaks of the functions. The superiority was confirmed for the samples of 20 different instruments based on the average width of the peaks. (C) 2011 Elsevier Ltd. All rights reserved.Article Citation - WoS: 36Citation - Scopus: 44Continuous Time Wavelet Entropy of Auditory Evoked Potentials(Elsevier Ltd., 2010) Çek, Mehmet Emre; Özgören, Murat; Savacı, Ferit Acar; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn this paper, the continuous time wavelet entropy (CTWE) of auditory evoked potentials (AEP) has been characterized by evaluating the relative wavelet energies (RWE) in specified EEG frequency bands. Thus, the rapid variations of CTWE due to the auditory stimulation could be detected in post-stimulus time interval. This approach removes the probability of missing the information hidden in short time intervals. The discrete time and continuous time wavelet based wavelet entropy variations were compared on non-target and target AEP data. It was observed that CTWE can also be an alternative method to analyze entropy as a function of time. © 2009 Elsevier Ltd. All rights reserved.Article Citation - WoS: 2Citation - Scopus: 2Determination of the Stationary State Densities of the Stochastic Nonlinear Dynamical Systems(Elsevier Ltd., 2006) Günel, Serkan; Savacı, Ferit Acar; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThe stationary state probability densities appear not only in the study of dynamical systems with random vector fields, but also in the deterministic dynamical systems exhibiting chaotic behavior when the uncertainties in the initial conditions are represented with the probability densities. But since it is very hard problem to determine these densities, in this paper the new efficient method to obtain an approximate solution of Fokker-Planck-Kolmogorov equation which arises in the determination of the stationary state probability densities has been given by representing the densities with compactly supported functions. With specific choice of the compactly supported functions as piecewise multivariable polynomials which are supported on the ellipsoidal regions, the parameters to be calculated for determining the densities can be considerably decreased compared to Multi-Gaussian Closure scheme, in which the stationary densities are assumed to be the weighted average of the Gaussian densities. The main motivation to choose the compactly supported functions is that, in the chaotic dynamics the states are trapped in a specific compact subspace of the state space. The stationary state densities of two basic examples commonly considered in the literature have been estimated using the Parzen's estimator, and the densities obtained using the newly proposed method have been compared with these estimated densities and the densities obtained with the Multi-Gaussian Closure scheme. The results indicate that the presented compactly supported piecewise polynomial scheme can be successful compared to Multi-Gaussian scheme, when the system is highly nonlinear.