支持向量机对舰船噪声DEMON谱的分类识别

本文采用径向基核函数的支持向量机的分类算法,实现了对舰船目标的分类识别。对两类不同类型的舰船的辐射噪声的DENOM谱建立了支持向量机模型,并进行了分类识别试验。试验结果表明,在结构风险最小的准则下,采用网格搜索法确定,径向基核函数的参数σ取值0.23、惩罚系数C值取13为最优的分类识别参数。并通过留一法验证,该模型具备良好的推广能力,总体正确识别率为91.2%。

Classification of the DEMON spectra of ship-radiated noise based on Support Vector Machine

In this paper, adoption of support vector machine with radial basis function kernel classification algorithm, succeed in realizing ship targets classification.Establish support vector machine models to two different rypies of ship-radiated noises DEMON spectrum, and the classified recognition experiment has been done.The experimental result indicates that, under the standard of structural risk minimization and adopting grid-search method, the radial basis function kernel parameter σ value 0.23 and the penalty parameter C value 13 are the most superior classification parameter.Meanwhile, this model has good capability in generalizing according to the validating by "leave-one-out" method, and the total correct identification probability is 91.2%.