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Investigation on optical, electrical and etching properties of 2-aminopyridinium 4-aminobenzoate: A phase matchable organic single crystal for optoelectronic device applications

Chandra L., Chandrasekaran J., Perumal K., Babu B., Jayaramakrishnan V.

Materials Science Poland

2017

Vol. 35, No. 1

126--134

NLO active 2-aminopyridinium 4-aminobenzoate (APAB) single crystals were successfully grown by the standard slow evaporation technique. The crystallinity of the grown crystals was analyzed through X-ray diffraction (XRD) measurements. Fourier transform infrared (FT-IR) spectroscopic studies were also performed for the identification of different modes present in the compound. The UV-Vis absorption and transmittance spectra were recorded for the grown crystal and the optical band gap was calculated. Birefringence and etching studies were also carried out. The dielectric study showed that the dielectric constant decreased with an increase in frequency. The photoconductivity study revealed its positive photoconducting nature. Theoretical HOMO LUMO investigations were also made for the crystal. The relative SHG efficiency of the material was investigated by the Kurtz and Perry powder technique. The phase matching property of the crystal was studied through the SHG dependence of average particle sizes.

TEO-CFCC Characteristic Parameter Extraction Method for Speaker Recognition in Noisy Environments

Li L., An D., Zhao D., Rong C., Ma S.

Przegląd Elektrotechniczny

2013

R. 89, nr 2a

118--121

This paper proposes TEO-CFCC characteristic parameter extraction method. Signal phase matching is applied to eliminate speech noise on the basis of CFCC characteristic parameter, and then Teager energy operator is added to the acquisition of CFCC characteristic parameter. In this way TEO-CFCC characteristic parameter is obtained and the energy of speech becomes one of the characteristic parameters for speaker recognition. Experiment results show that the recognition accuracy can reach to 83.2% in a -5dB SNR of vehicle interior noise environment by using TEO-CFCC characteristic parameter.

W artykule przedstawiono metodę wyznaczania parametrów charakterystycznych filtru TEO-CFCC. Zastosowano tu dopasowywanie fazowe sygnału, dla eliminacji z mowy szumów oraz operator Teagera do wyrugowania parametrów. Badania eksperymentalne pokazuję, że dokładność rozpoznania głosu wynosi 83,2% przy -5dB SNR we wnętrzu pojazdu.