欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对线性的互信息特征提取方法,通过研究互信息梯度在核空间中的线性不变性,提出一种快速、高效的非线性特征提取方法。该方法采用互信息二次熵快速算法及梯度上升的寻优策略,提取有判别能力的非线性高阶统计量;在计算时避免传统非线性特征提取中的特征值分解运算,有效降低计算量。通过UCT数据的投影和分类实验表明,该方法无论在投影空间的可分性上,还是在算法时间复杂度上,都明显优于传统算法。
英文摘要：
This paper proposed a fast and effective method of nonlinear feature extraction by studying the linear invariance of mutual information gradient in the linear mutual information feature extraction. It employed a fast algorithm for mutual information and gradient ascent which avoid the eigenvalue decomposition of the traditional nonlinear transformation. In this way,the extracted features could reflect the characteristics of discriminative higher-order statistics,and effectively reduce the computational complexity. Experiments with the UCI read data show that the proposed approach performs well in projection and classification performance,and is better than traditional nonlinear algorithms for the time complexity.
同期刊论文项目
同项目期刊论文
Recovering missing pixels for Landsat ETM plus SLC-off imagery using multi-temporal regression analy
An Adaptive Artificial Immune Network for Supervised Classification of Multi-/Hyperspectral Remote S
A Kernel-Based Target-Constrained Interference-Minimized Filter for Hyperspectral Sub-Pixel Target D
An Endmember Dissimilarity Constrained Non-Negative Matrix Factorization Method for Hyperspectral Un
A Perceptually Inspired Variational Method for the Uneven Intensity Correction of Remote Sensing Ima
SAR image denoising in nonsubsampled contourlet transform domain based on maximum a posteriori and n
A modified stochastic neighbor embedding for multi-feature dimension reduction of remote sensing ima
期刊信息
位置：