A novel key-dependent audio fingerprinting technique is proposed by introducing the quantisation minimum distance (QMD) as a hash extractor in the discrete wavelet transform (DWT) domain. The quantiser dithers of the QMD are generated using a chaotic map whose initial value is used as a secret key for fingerprint extraction. Experimental results show that the proposed audio fingerprinting technique achieves with a small fingerprint size an excellent discrimination between audio signals of different contents and outperforms the existing Philips robust hash based techniques in terms of the robustness.
This study presents the characterization of the nickel–vanadium (NiV) Schottky diode on n-type silicon (Si) in the temperature range 75 K–300 K. The experimental current–voltage (I–V) measurements are first analyzed by using the thermionic emission (TE) theory. For this purpose, the vertical optimization method is used to find the values of the TE parameters, i.e. the values of the ideality factor, barrier height, and series resistance. It is found that these parameters exhibit strong temperature dependence, i.e. an increase of the ideality factor and a decrease of the barrier height ϕ B and the series resistance R s when the temperature decreases, which is due to inhomogeneities at the Schottky interface. Therefore, we employ Werner’s model under the assumption of a Gaussian distribution to analyze the temperature dependence of the TE parameters. The mean and standard deviation of the barrier height are obtained as ϕ B 0 = 0.68 eV and σ 0 = 53.665 , respectively. In addition, we show that the apparent barrier height and apparent ideality factor are in accordance with Werner’s model. Furthermore, we use the modified Richardson plot to find the value of the Richardson constant. The obtained value of the latter is A ∗ = 111.56 A cm−2 K−2 and is very close to the theoretical value of 112 A cm−2 K−2 of n-type Si. Finally, we investigate the temperature dependence of the ideality factor and show the validity of the T0-effect for the NiV/Si Schottky diode.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.