基于流形学习和SVM的储粮害虫声信号识别研究

声检测法能够快速检测粮虫，对提早防治储粮害虫具有十分重要的作用.研究了2种储粮害虫的4种活动声信号，利用流形学习的等距特征映射方法对声信号进行降维并提取流形特征，采用以重尾径向基为核函数的SVM训练最优分类面，对流形特征数据进行测试和识别分类.实验结果表明，等距特征映射方法能够有效提取2种储粮害虫声信号的流形特征，且SVM的分类识别效果良好.

Research on acoustic signals recognition of stored graininsects based on manifold learning and SVM

Acoustic method can detect stored grain insects quickly and plays a very important role in preventing grain insects early.Four kinds of active acoustic signals of two varieties of grain insects were studied.Using isometric feature mapping method of manifold learning,dimensions were reduced and manifold characteristics of acoustic signals were extracted.Then optimal separate hyperplane was trained by SVM with heavy tailed radial basis function as kernel function.It can test and recognize manifold characteristics.The result demonstratesd that isometric feature mapping method can extract manifold characteristics of acoustic signals of two kinds of grain insects.SVM classifies and recognizes manifold characteristics well.