为了将高维富模型特征投影与分类器结合,降低隐写图像的检测误差,提出对高维富模型特征分割再结合混合核的特征投影算法的隐写分析方法。将高维特征纵向分解为若干特征块,对每个特征块投影,投影后的特征块拼成新的特征。设计非线性混合...为了将高维富模型特征投影与分类器结合,降低隐写图像的检测误差,提出对高维富模型特征分割再结合混合核的特征投影算法的隐写分析方法。将高维特征纵向分解为若干特征块,对每个特征块投影,投影后的特征块拼成新的特征。设计非线性混合核函数代替单核函数进行特征投影,以克服样本规模巨大、多维数据的不规则等现象。投影后的特征用FLD(Fisher Linear Discriminant)集成分类器分类。实验结果表明,该方法进一步降低了隐写图像的检测错误率,同时有效降低了运行内存需求。展开更多
Based on continuum power regression(CPR) method, a novel derivation of kernel partial least squares(named CPR-KPLS) regression is proposed for approximating arbitrary nonlinear functions.Kernel function is used to map...Based on continuum power regression(CPR) method, a novel derivation of kernel partial least squares(named CPR-KPLS) regression is proposed for approximating arbitrary nonlinear functions.Kernel function is used to map the input variables(input space) into a Reproducing Kernel Hilbert Space(so called feature space),where a linear CPR-PLS is constructed based on the projection of explanatory variables to latent variables(components). The linear CPR-PLS in the high-dimensional feature space corresponds to a nonlinear CPR-KPLS in the original input space. This method offers a novel extension for kernel partial least squares regression(KPLS),and some numerical simulation results are presented to illustrate the feasibility of the proposed method.展开更多
An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into...An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into wavelet technique in support vector machine(SVM).Since manifold wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities,the MWSVM can approximate arbitrary nonlinear functions and forecast stock returns accurately.The applicability and validity of MWSVM for stock returns forecasting is confirmed through experiments on real-world stock data.展开更多
文摘为了将高维富模型特征投影与分类器结合,降低隐写图像的检测误差,提出对高维富模型特征分割再结合混合核的特征投影算法的隐写分析方法。将高维特征纵向分解为若干特征块,对每个特征块投影,投影后的特征块拼成新的特征。设计非线性混合核函数代替单核函数进行特征投影,以克服样本规模巨大、多维数据的不规则等现象。投影后的特征用FLD(Fisher Linear Discriminant)集成分类器分类。实验结果表明,该方法进一步降低了隐写图像的检测错误率,同时有效降低了运行内存需求。
文摘Based on continuum power regression(CPR) method, a novel derivation of kernel partial least squares(named CPR-KPLS) regression is proposed for approximating arbitrary nonlinear functions.Kernel function is used to map the input variables(input space) into a Reproducing Kernel Hilbert Space(so called feature space),where a linear CPR-PLS is constructed based on the projection of explanatory variables to latent variables(components). The linear CPR-PLS in the high-dimensional feature space corresponds to a nonlinear CPR-KPLS in the original input space. This method offers a novel extension for kernel partial least squares regression(KPLS),and some numerical simulation results are presented to illustrate the feasibility of the proposed method.
基金the Hunan Natural Science Foundation(No. 09JJ3129)the Hunan Key Social Science Foundation (No. 09ZDB04)the Hunan Social Science Foundation (No. 08JD28)
文摘An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into wavelet technique in support vector machine(SVM).Since manifold wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities,the MWSVM can approximate arbitrary nonlinear functions and forecast stock returns accurately.The applicability and validity of MWSVM for stock returns forecasting is confirmed through experiments on real-world stock data.
