中文说明：通过将极限学习机（ELM）和稀疏表示（SRC）结合到统一框架中，所提出的混合分类器不仅具有快速测试（ELM的优点）的优点，而且显示出显着的分类精度（SRC的优点）。测试它的AR面部识别，它达到95％的高精度，比ELM（91％）和SRC（93.5％）更好。ELM和SRC之间的桥梁是ELM错误分类度量和自适应选择。
English Description：
By combining extreme learning machine (ELM) and sparse representation (SRC) into a unified framework, the proposed hybrid classifier not only has the advantages of fast testing (ELM), but also shows significant classification accuracy (SRC). Test its ar face recognition, it achieves 95% high accuracy, better than elm (91%) and SRC (93.5%). The bridge between elm and Src is elm error classification measurement and adaptive selection.