期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Pretreating near infrared spectra with fractional order Savitzky–Golay differentiation(FOSGD) 被引量:4
1
作者 Kai-Yi Zheng Xuan Zhang +2 位作者 Pei-Jin Tong Yuan Yao Yi-Ping Du 《Chinese Chemical Letters》 SCIE CAS CSCD 2015年第3期293-296,共4页
With the aid of Riemann–Liouville fractional calculus theory,fractional order Savitzky–Golay differentiation(FOSGD) is calculated and applied to pretreat near infrared(NIR) spectra in order to improve the perfor... With the aid of Riemann–Liouville fractional calculus theory,fractional order Savitzky–Golay differentiation(FOSGD) is calculated and applied to pretreat near infrared(NIR) spectra in order to improve the performance of multivariate calibrations.Similar to integral order Savitzky–Golay differentiation(IOSGD),FOSGD is obtained by fitting a spectral curve in a moving window with a polynomial function to estimate its coefficients and then carrying out the weighted average of the spectral curve in the window with the coefficients.Three NIR datasets including diesel,wheat and corn datasets were utilized to test this method.The results showed that FOSGD,which is easy to compute,is a general method to obtain Savitzky–Golay smoothing,fractional order and integral order differentiations.Fractional order differentiation computation to the NIR spectra often improves the performance of the PLS model with smaller RMSECV and RMSEP than integral order ones,especially for physical properties of interest,such as density,cetane number and hardness. 展开更多
关键词 Golay FOSGD fractional fitting smoothing utilized compute polynomial Liouville calibration
原文传递
A Useful Extension of It 's Formula with Applications to Optimal Stopping
2
作者 GeroldALSMEYER MarkusJAEGER 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2005年第4期779-786,共8页
Given a continuous semimartingale M = (Mt)t≥〉0 and a d-dimensional continuous process of locally bounded variation V = (V^1,……, V^d), the multidimensional Ito Formula states that f(Mt, Vt) - f(M0, V0) = ... Given a continuous semimartingale M = (Mt)t≥〉0 and a d-dimensional continuous process of locally bounded variation V = (V^1,……, V^d), the multidimensional Ito Formula states that f(Mt, Vt) - f(M0, V0) = ∫[0, t] Dx0f(Ms, Vs)dMs+∑i=1^d∫[0, t] Dxi F(Ms, Vs)dVs^i+1/2∫[0, t] Dx0^2 f(Ms, Vs)d 〈M〉s if f(x0,……,xd) is of C^2-type with respect to x0 and of C^1-type with respect to the other arguments This formula is very useful when solving various optimal stopping problems based on Brownian motion. However, in such application the function f typically fails to satisfy the stated conditions in that its first partial derivative with respect to x0 is only absolutely continuous. We prove that the formula remains true for such functions and demonstrate its use with two examples from Mathematical Finance. 展开更多
关键词 Multidimensional Ito Formula Continuous semimartingale Brownian motion Geometric Brownian motion Optimal stopping Smooth fit principle American put option
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部