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基于车辆声音及震动信号相融合的车型识别 被引量:4
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作者 焦琴琴 牛力瑶 孙壮文 《微型机与应用》 2015年第11期79-82,共4页
车型识别技术是智能运输系统的核心。针对目前车型识别方法的不足,提出了一种基于车辆声音和震动信号相融合的车型识别方法。用BCS算法提取声震信号的特征,并在特征级融合形成特征向量,以此作为训练样本对支持向量机的分类器进行训练。... 车型识别技术是智能运输系统的核心。针对目前车型识别方法的不足,提出了一种基于车辆声音和震动信号相融合的车型识别方法。用BCS算法提取声震信号的特征,并在特征级融合形成特征向量,以此作为训练样本对支持向量机的分类器进行训练。对两种车型的声音和震动数据进行处理的结果表明,基于特征级融合的声震信号能够准确识别不同的车型,识别准确率达到86%以上,是一种有效的车型识别方法。 展开更多
关键词 车型识别 声震信号 特征融合 支持向量机
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基于改进TCN模型的野外运动目标分类 被引量:3
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作者 范裕莹 李成娟 +1 位作者 易强 李宝清 《计算机工程》 CAS CSCD 北大核心 2021年第9期106-112,共7页
野外运动目标信号的背景噪声复杂,利用单模态声音信号进行野外目标分类识别率低且鲁棒性差。针对该问题,提出一种基于声震多模态融合的网络模型。借鉴DenseNet网络密集连接的思想改进时域卷积网络,从而对四通道声音信号和单通道震动信... 野外运动目标信号的背景噪声复杂,利用单模态声音信号进行野外目标分类识别率低且鲁棒性差。针对该问题,提出一种基于声震多模态融合的网络模型。借鉴DenseNet网络密集连接的思想改进时域卷积网络,从而对四通道声音信号和单通道震动信号进行深层次的特征提取,并将两种信号相互融合得到最终的目标分类结果。同时,使用带权重的损失函数解决因数据不均衡导致的泛化性能差的问题。实验结果表明,融合网络的识别准确率达到92.92%,较单模态输入网络提高了6.63%~9.46%,且该网络具有较强的鲁棒性。 展开更多
关键词 声震信号 多模态融合 时域卷积网络 密集连接 运动目标分类
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Seismic noise attenuation using nonstationary polynomial fitting 被引量:12
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作者 Liu Guo-Chang Chen Xiao-Hong +2 位作者 Li Jing-Ye Du Jing Song Jia-Wen 《Applied Geophysics》 SCIE CSCD 2011年第1期18-26,94,共10页
We propose a novel method for seismic noise attenuation by applying nonstationary polynomial fitting (NPF), which can estimate coherent components with amplitude variation along the event. The NPF with time-varying ... We propose a novel method for seismic noise attenuation by applying nonstationary polynomial fitting (NPF), which can estimate coherent components with amplitude variation along the event. The NPF with time-varying coefficients can adaptively estimate the coherent components. The smoothness of the polynomial coefficients is controlled by shaping regularization. The signal is coherent along the offset axis in a common midpoint (CMP) gather after normal moveout (NMO). We use NPF to estimate the effective signal and thereby to attenuate the random noise. For radial events-like noise such as ground roll, we first employ a radial trace (RT) transform to transform the data to the time-velocity domain. Then the NPF is used to estimate coherent noise in the RT domain. Finally, the coherent noise is adaptively subtracted from the noisy dataset. The proposed method can effectively estimate coherent noise with amplitude variations along the event and there is no need to propose that noise amplitude is constant. Results of synthetic and field data examples show that, compared with conventional methods such as stationary polynomial fitting and low cut filters, the proposed method can effectively suppress seismic noise and preserve the signals. 展开更多
关键词 Polynomial fitting noise attenuation radial trace transform nonstationary regression
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Giant-Resonance for a Four-Dimensionally Coupled System with Dichotomous Noise
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作者 LI Jing-Hui HAN Yin-Xia 《Communications in Theoretical Physics》 SCIE CAS CSCD 2007年第4期672-674,共3页
In this paper, we investigate a four-dimensionally coupled system driven by dichotomous noise. A new kind of stochastic resonance is found, for which the response of the system to the input signal can be hugely intens... In this paper, we investigate a four-dimensionally coupled system driven by dichotomous noise. A new kind of stochastic resonance is found, for which the response of the system to the input signal can be hugely intensified. 展开更多
关键词 super-conducting junction electron pairs spatial-temporal noise
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