Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Article Citation - WoS: 23A Quasi-Distributed Temperature Sensor Interrogated by Optical Frequency-Domain Reflectometer(IOP Publishing Ltd., 2011) Yüksel, Kıvılcım; Mégret, Patrice; Wuilpart, MarcThis paper presents the analysis of a quasi-distributed sensor based on the concatenation of identical low-reflective fiber Bragg gratings. We experimentally demonstrated a temperature sensor using ten cascaded gratings which are interrogated by an optical frequency domain reflectometer. Repeatability measurements highlighted a standard deviation on the measured temperature smaller than 1.5 °C. A complete demonstration of mathematical formulas which are used to obtain the temperature information is also provided. © 2011 IOP Publishing Ltd.Article Citation - WoS: 97Analysis and Suppression of Nonlinear Frequency Modulation in an Optical Frequency-Domain Reflectometer(The Optical Society, 2009) Yüksel, Kıvılcım; Wuilpart, Marc; Mégret, PatriceA new method for monitoring the nonlinearities perturbing the optical frequency sweep in high speed tunable laser sources is presented. The swept-frequency monitoring system comprises a Mach-Zehnder interferometer and simple signal processing steps. It has been implemented in a coherent optical frequency domain reflectometer which allowed to drastically reduce the effects of nonlinear sweep, resulting to a spatial resolution enhancement of 30 times. © 2009 Optical Society of America.Conference Object Citation - WoS: 7Citation - Scopus: 11Noise Robust Speaker Verification Using Mel-Frequency Discrete Wavelet Coefficients and Parallel Model Compensation(Institute of Electrical and Electronics Engineers Inc., 2005) Tüfekçi, Zekeriya; Gürbüz, SabriInterfering noise severely degrades the performance of a speaker verification system. The Parallel Model Combination (PMC) technique is one of the most efficient techniques for dealing with such noise. Another method is to use features local in the frequency domain. Recently, Mel-Frequency Discrete Wavelet Coefficients (MFDWCs) [1, 2] were proposed as speech features local in frequency domain. In this paper, we discuss using PMC along with MFDWCs features to take advantage of both noise compensation and local features (MFDWCs) to decrease the effect of noise on speaker verification performance. We evaluate the performance of MFDWCs using the NIST 1998 speaker recognition and NOISEX-92 databases for various noise types and noise levels. We also compare the performance of these versus MFCCs and both using PMC for dealing with additive noise. The experimental results show significant performance improvements for MFDWCs versus MFCCs after compensating the Gaussian Mixture Models (GMMs) using the PMC technique. The MFDWCs gave 5.24 and 3.23 points performance improvement on average over MFCCs for -6 dB and 0 dB SNR values, respectively. These correspond to 26.44% and 23.73% relative reductions in equal error rate (EER), respectively.