CAJ | 학술논문

针对目前冲击声识别系统稳健性较差问题，提出一种基于贝叶斯压缩感知（BCS）的冲击声识别方法。该方法基于BCS模型，根据训练样本构造传感矩阵；基于稀疏系数的分布特性设计分类算法完成目标识别；将提出的方法与传统分类算法的识别结果做了对比和分析。实验结果表明：提出的方法能够对识别相似冲击声进行精确分类，识别精度和抗噪性均优于SVM和GMM分类算法。
침대목전충격성식별계통은건성교차문제，제출일충기우패협사압축감지（BCS）적충격성식별방법。해방법기우BCS모형，근거훈련양본구조전감구진；기우희소계수적분포특성설계분류산법완성목표식별；장제출적방법여전통분류산법적식별결과주료대비화분석。실험결과표명：제출적방법능구대식별상사충격성진행정학분류，식별정도화항조성균우우SVM화GMM분류산법。
For the poor robustness of impact sounds recognition system available,an impulsive sound recognition method based on Bayesian compressive sensing(BCS)is proposed. The method is based on the BCS model. The sensing matrix is con-structed by the training samples. The target recognition is accomplished by designing sorting algorithm on the basis of distribu-tion character of sparse coefficient. The recognition results from the new method and traditional classification algorithm are com-pared and analyzed. The experimental results show that the method can accurately distinguish sounds with very similar properties and outperforms the SVM and GMM methods in recognition precision and noise immunity.