A method to estimate the probabilistic density function （PDF） of shear strength parameters was proposed. The second Chebyshev orthogonal polynomial（SCOP） combined with sample moments （the origin moments） was use...A method to estimate the probabilistic density function （PDF） of shear strength parameters was proposed. The second Chebyshev orthogonal polynomial（SCOP） combined with sample moments （the origin moments） was used to approximate the PDF of parameters. X^2 test was adopted to verify the availability of the method. It is distribution-free because no classical theoretical distributions were assumed in advance and the inference result provides a universal form of probability density curves. Six most commonly-used theoretical distributions named normal, lognormal, extreme value Ⅰ , gama, beta and Weibull distributions were used to verify SCOP method. An example from the observed data of cohesion c of a kind of silt clay was presented for illustrative purpose. The results show that the acceptance levels in SCOP are all smaller than those in the classical finite comparative method and the SCOP function is more accurate and effective in the reliability analysis of geotechnical engineering.展开更多
We introduce a novel coarse ridge orientation smoothing algorithm based on orthogonal polynomials, which can be used to estimate the orientation field (OF) for fingerprint areas of no ridge information. This method do...We introduce a novel coarse ridge orientation smoothing algorithm based on orthogonal polynomials, which can be used to estimate the orientation field (OF) for fingerprint areas of no ridge information. This method does not need any base information of singular points (SPs). The algorithm uses a consecutive application of filtering-and model-based orientation smoothing methods. A Gaussian filter has been employed for the former. The latter conditionally employs one of the orthogonal polynomials such as Legendre and Chebyshev type I or II, based on the results obtained at the filtering-based stage. To evaluate our proposed method, a variety of exclusive fingerprint classification and minutiae-based matching experiments have been conducted on the fingerprint images of FVC2000 DB2, FVC2004 DB3 and DB4 databases. Results showed that our proposed method has achieved higher SP detection, classification, and verification performance as compared to competing methods.展开更多
基金Projects(50490274 , 10472134 , 50404010) supported by the National Natural Science Foundation of China project(2002CB412703) supported by the Key Fundamental Research and Development Programof China
文摘A method to estimate the probabilistic density function （PDF） of shear strength parameters was proposed. The second Chebyshev orthogonal polynomial（SCOP） combined with sample moments （the origin moments） was used to approximate the PDF of parameters. X^2 test was adopted to verify the availability of the method. It is distribution-free because no classical theoretical distributions were assumed in advance and the inference result provides a universal form of probability density curves. Six most commonly-used theoretical distributions named normal, lognormal, extreme value Ⅰ , gama, beta and Weibull distributions were used to verify SCOP method. An example from the observed data of cohesion c of a kind of silt clay was presented for illustrative purpose. The results show that the acceptance levels in SCOP are all smaller than those in the classical finite comparative method and the SCOP function is more accurate and effective in the reliability analysis of geotechnical engineering.
文摘We introduce a novel coarse ridge orientation smoothing algorithm based on orthogonal polynomials, which can be used to estimate the orientation field (OF) for fingerprint areas of no ridge information. This method does not need any base information of singular points (SPs). The algorithm uses a consecutive application of filtering-and model-based orientation smoothing methods. A Gaussian filter has been employed for the former. The latter conditionally employs one of the orthogonal polynomials such as Legendre and Chebyshev type I or II, based on the results obtained at the filtering-based stage. To evaluate our proposed method, a variety of exclusive fingerprint classification and minutiae-based matching experiments have been conducted on the fingerprint images of FVC2000 DB2, FVC2004 DB3 and DB4 databases. Results showed that our proposed method has achieved higher SP detection, classification, and verification performance as compared to competing methods.
