计算机与数字工程2017，Vol.45Issue(5)：807-811,843,6.DOI:10.3969/j.issn.1672-9722.2017.05.004
基于双权重约束的判别字典学习算法
Discriminative Dictionary Learning Based on the Double Weighted Constraints
摘要
Abstract
In order to improve the classification performance of dictionary learning algorithms,a double weighted constraints discriminative dictionary learning algorithm(DWCDL)is proposed. The weighted constraint of atoms is constructed by using the pro?files,and it not only encourages the similar atoms to reconstruct training samples of the same class,but reduces the coherence of at?oms. The weighted constraint of coding coefficients is constructed by using the label information of training samples,and it can en?courage the training sample of the same class to have similar coding coefficients. Experimental results show that the proposed algo?rithm can achieve better classification performance than seven sparse coding and dictionary learning algorithms.关键词
字典学习/权重约束/图像分类Key words
dictionary learning/weighted constraint/image classification分类
信息技术与安全科学引用本文复制引用
李争名,杨南粤..基于双权重约束的判别字典学习算法[J].计算机与数字工程,2017,45(5):807-811,843,6.基金项目
国家自然科学基金项目(编号:61370613,61573248) （编号:61370613,61573248）
广东省普通高校青年创新人才项目(编号:2015KQNCX089)资助. （编号:2015KQNCX089）
