关键词: 自适应权重, 多重稀疏表示, 稀疏表示分类器（SRC）

Abstract: An adaptive weighted multiple?sparse representation classification method is proposed in this paper. To address the weak discriminative power of the conventional SRC （Sparse Representation Classifier） method which uses a single feature representation, it proposes using multiple features to represent each sample and construct multiple feature sub-dictionaries for classification. To reflect the different importance and discriminative power of each feature, it presents an adaptive weighted method to linearly combine different feature representations for classification. Experimental results demonstrate the effectiveness of the proposed method and better classification accuracy can be obtained than the conventional SRC method.

Key words: adaptive weight, multiple sparse representation, Sparse Representation Classifier（SRC）