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| 1 | 基于多特征融合的SVM声学场景分类算法研究显示文摘针对DCASE2017挑战赛的声场环境数据集,提取梅尔频率倒谱系数(MFCC)、短时能量(SE)、声学事件似然特征(AELF)、静音时间(MT)特征,组成多特征融合矩阵,通过对比多种核函数和寻优算法,最终选取高斯径向基核函数(RK)建立支持向量机(SVM)模型,采用交叉验证(CV)方法进行SVM参数寻优,对15种声学场景进行分类.实验结果表明,杂货店、办公室的分类准确性达到了90%以上,平均分类准确性达到71.11%,远高于挑战赛的基线系统61%的平均分类准确性. | 赵薇 靳聪 涂中文 SRIDHAR Krishnan 刘杉 | 2020 | 北京理工大学学报2020，40，1： | 13 |
| 2 | Compressed Sensing In Wireless Sensor Networks:Survey显示文摘 | Mohammadreza Balouchestani Kaamran Raahemifar and Sridhar Krishnan | 2011 | CanadianJouranl on Multimedia andWireless Networks2011，2，1： | 1 |
| 3 | Time-Frequency Matrix Feature Extraction and Classification of Environmental Audio Signals显示文摘 | Behnaz Ghoraani J Sridhar Krishnan | | 0，，07： | 1 |
| 4 | Wavelet-based sparse functional linear model with applications to EEGs seizure detection and epilepsy diagnosis显示文摘 | Shengkun Xie Sridhar Krishnan | 2013 | Medical & Biological Engineering & Computing2013，，1： | 1 |
| 5 | Visual saliency’s modulatory effect on just noticeable distortion profile and its application in image watermarking显示文摘 | Yaqing Niu Matthew Kyan Lin Ma Azeddine Beghdadi Sridhar Krishnan | 2012 | Signal Processing: Image Communication2012，，： | 1 |
| 6 | Creating Growth with Services 显示文摘 | Sawhney Mohanbir Balasubramanian Sridhar Krishnan Vish V | 2004 | MIT Sloan Management Review2004，，2： | 1 |
| 7 | Detection of Chondromalacia Patellae by Analysis of Intrinsic Mode Functions in Knee-Joint Vibration Signals显示文摘This paper presents the knee-joint vibration signal processing and pathological localization procedures using the empirical mode decomposition for patients with chondrom alacia patellae.The artifacts of baseline wander and random noise were identified in the decomposed monotonic trend and intrinsic mode functions (IMF) using the modeling method of probability density function and the confidence limit criterion.Then, the fluctuation parts in the signal were detected by the signal method turning for count. The results demonstrated that the quality of reconstructed signal can be greatly improved, with the removal of the baseline wander(adaptive trend) and the Gaussian distributed random noise. By detecting the turn signals in the artifact-free signal, the pathological segments related to chondrom alacia patellae can be effectively localized with the beginning and ending points of the span of turn signals. | WU Yun-feng CAI Su-xian XU Fang SHI Lei Sridhar Krishnan | 2014 | Chinese Journal of Biomedical Engineering(English Edition)2014，23，2： | 1 |
| 8 | Real-Time Classi- fication of Forearm Electromyographic Signals Corresponding to User-Selected Intentional Movements for Muhifunction Prosthesis Control显示文摘 | Kaveh Momen Sridhar Krishnan Tom Chau | 2007 | IEEE Transactions on neural systems and rehabilita- tion engineering2007，15，4： | 1 |
| 9 | Rationing capacity between two products classes 显示文摘 | Bal Krishnan N Sridhar an S V Patterson J W | 1996 | Decision Sciences1996，27，2： | 1 |
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