The electronic structures,chemical bonding,elastic and optical properties of the novel hP24 phase WB3 were investigated by using density-functional theory(DFT) within generalized gradient approximation(GGA).The calcul...The electronic structures,chemical bonding,elastic and optical properties of the novel hP24 phase WB3 were investigated by using density-functional theory(DFT) within generalized gradient approximation(GGA).The calculated energy band structures show that the hP24 phase WB3 is metallic material.The density of state(DOS) and the partial density of state(PDOS) calculations show that the DOS near the Fermi level is mainly from the W 5d and B 2p states.Population analysis suggests that the chemical bonding in hP24-WB3 has predominantly covalent characteristics with mixed covalent-ionic characteristics.Basic physical properties,such as lattice constant,bulk modulus,shear modulus and elastic constants Cij were calculated.The elastic modulus E and Poisson ratio υ were also predicted.The results show that hP24-WB3 phase is mechanically stable and behaves in a brittle manner.Detailed analysis of all optical functions reveals that WB3 is a better dielectric material,and reflectivity spectra show that WB3 can be promised as good coating material in the energy regions of 8.5-11.4 eV and 14.5-15.5 eV.展开更多
In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is propose...In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is proposed in this paper.The animal sound is turned into spectrogram to show the energy,time and frequency characteristics.The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution(SPD)and sub-band division.Radon transform(RT)and discrete wavelet transform(DWT)are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature.The E-F feature is formed by combining the SPD feature and sub-band energy value feature.The classification is achieved by support vector machine(SVM)classifier.The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.展开更多
基金Project(11271121)supported by the National Natural Science Foundation of ChinaProject(11JJ2002)supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(11K038)supported by Key Laboratory of Computational and Stochastic Mathematics of Ministry of Education of ChinaProject(2013GK3130)supported by the Scientific and Technological Plan of Hunan Province,China
文摘The electronic structures,chemical bonding,elastic and optical properties of the novel hP24 phase WB3 were investigated by using density-functional theory(DFT) within generalized gradient approximation(GGA).The calculated energy band structures show that the hP24 phase WB3 is metallic material.The density of state(DOS) and the partial density of state(PDOS) calculations show that the DOS near the Fermi level is mainly from the W 5d and B 2p states.Population analysis suggests that the chemical bonding in hP24-WB3 has predominantly covalent characteristics with mixed covalent-ionic characteristics.Basic physical properties,such as lattice constant,bulk modulus,shear modulus and elastic constants Cij were calculated.The elastic modulus E and Poisson ratio υ were also predicted.The results show that hP24-WB3 phase is mechanically stable and behaves in a brittle manner.Detailed analysis of all optical functions reveals that WB3 is a better dielectric material,and reflectivity spectra show that WB3 can be promised as good coating material in the energy regions of 8.5-11.4 eV and 14.5-15.5 eV.
基金Supported by the National Natural Science Foundation of China(No.61075022)
文摘In the natural environment,non-stationary background noise affects the animal sound recognition directly.Given this problem,a new technology of animal sound recognition based on energy-frequency(E-F)feature is proposed in this paper.The animal sound is turned into spectrogram to show the energy,time and frequency characteristics.The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution(SPD)and sub-band division.Radon transform(RT)and discrete wavelet transform(DWT)are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature.The E-F feature is formed by combining the SPD feature and sub-band energy value feature.The classification is achieved by support vector machine(SVM)classifier.The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.
