针对农田监测区域大、监测节点能量有限以及异常事件具有偶发性等特点,提出了一种基于改进压缩采样匹配追踪的农田信息异常事件检测算法(DP-CoSaMP)。针对传统压缩采样匹配追踪(Compressive sampling matching pursuit,Co Sa MP)算法中...针对农田监测区域大、监测节点能量有限以及异常事件具有偶发性等特点,提出了一种基于改进压缩采样匹配追踪的农田信息异常事件检测算法(DP-CoSaMP)。针对传统压缩采样匹配追踪(Compressive sampling matching pursuit,Co Sa MP)算法中相似原子选择和稀疏度要求已知问题,引进Dice系数有效区分原子相关性,保证选择最优原子;利用峰值信噪比(Peak signal to noise ratio,PSNR)与匹配信号残差具有相似变化趋势,动态调整算法迭代次数,避免稀疏度获取困难问题。仿真实验结果表明,本文算法异常事件检测成功率较现有算法提高了20%,网络能耗降低了15%,平均检测时间减少了50%。展开更多
为有效解决压缩采样匹配追踪(compressive sampling matching pursuit,Co Sa MP)算法对稀疏度K值的依赖问题,提高重构精度,提出了一种根据峰值信噪比增减变化趋势来确定最佳迭代次数的Co Sa MP改进算法。先将PSNR算式进行数学推导演变,...为有效解决压缩采样匹配追踪(compressive sampling matching pursuit,Co Sa MP)算法对稀疏度K值的依赖问题,提高重构精度,提出了一种根据峰值信噪比增减变化趋势来确定最佳迭代次数的Co Sa MP改进算法。先将PSNR算式进行数学推导演变,将算式中未知的原始信号巧妙转换为已知信号,并证明了此转换式与PSNR算式有相同增减性,在迭代过程中基于此转换式可根据各列稀疏度的不同,自适应地确定不同列的最佳迭代次数,从而保证更高的重构精度。理论分析和实验仿真表明,改进的Co Sa MP算法比原有算法有更理想的重构效果,与其他重构算法相比有更高的重构成功率,并且更具高效性和实用性。展开更多
以稀疏表示理论为出发点,分析信号的压缩感知理论与传统Nyquist采样定理的理论对比结果,根据Co Sa MP算法和IFFT信号重构结果,定性和定量地分析了信号内部冗余性与利用这种冗余特征进行减运算量处理的可行性,进一步探讨信号的非均匀化处...以稀疏表示理论为出发点,分析信号的压缩感知理论与传统Nyquist采样定理的理论对比结果,根据Co Sa MP算法和IFFT信号重构结果,定性和定量地分析了信号内部冗余性与利用这种冗余特征进行减运算量处理的可行性,进一步探讨信号的非均匀化处理,包括分数域和分形等方法在信号处理领域的适应性。展开更多
Compressive sampling matching pursuit （CoSaMP） algorithm integrates the idea of combining algorithm to ensure running speed and provides rigorous error bounds which provide a good theoretical guarantee to convergenc...Compressive sampling matching pursuit （CoSaMP） algorithm integrates the idea of combining algorithm to ensure running speed and provides rigorous error bounds which provide a good theoretical guarantee to convergence. And compressive sensing （CS） can help us ease the pressure of hardware facility from the requirements of the huge amount in information processing. Therefore, a new video coding framework was proposed, which was based on CS and curvelet transform in this paper. Firstly, this new framework uses curvelet transform and CS to the key frame of test sequence, and then gains recovery frame via CoSaMP to achieve data compress. In the classic CoSaMP method, the halting criterion is that the number of iterations is fixed. Therefore, a new stopping rule is discussed to halting the algorithm in this paper to obtain better performance. According to a large number of experimental results, we ran see that this new framework has better performance and lower RMSE. Through the analysis of the experimental data, it is found that the selection of number of measurements and sparsity level has great influence on the new framework. So how to select the optimal parameters to gain better performance deserves worthy of further study.展开更多
考虑到井下应急救灾的需要,设计了一种基于压缩感知和无线传感器网络(WSNs)的矿井应急语音通信系统。根据语音信号的稀疏性,采用压缩感知的方法,对语音信号进行随机采样并传输,在Sink接收端,分别利用OMP算法和Co Sa MP算法进行信号重构...考虑到井下应急救灾的需要,设计了一种基于压缩感知和无线传感器网络(WSNs)的矿井应急语音通信系统。根据语音信号的稀疏性,采用压缩感知的方法,对语音信号进行随机采样并传输,在Sink接收端,分别利用OMP算法和Co Sa MP算法进行信号重构,对比仿真实验表明:Co Sa MP重构效果较好。考虑到井下无线信号传输受限,进行了井下无线通信实验,表明在通信距离为20 m情况下,可实时可靠地实现井下应急语音通信。展开更多
提出了一种基于双密度双树复小波(double-density dual-tree complex wavelet transform,DDDT-CWT)基的结构化CS图像重构算法,该算法将图像在双密度双树复小波变换下的系数呈现的树结构化特征与Co Sa MP重构算法相结合,实现了对原始图...提出了一种基于双密度双树复小波(double-density dual-tree complex wavelet transform,DDDT-CWT)基的结构化CS图像重构算法,该算法将图像在双密度双树复小波变换下的系数呈现的树结构化特征与Co Sa MP重构算法相结合,实现了对原始图像的更精确重构.实验结果表明:在相同压缩比的前提下,与传统使用DWT基且未考虑变换系数结构化特征的重构算法相比,使用DDDT-CWT基和融入结构化特征的重构算法分别可获得2.9～3.2 d B与0.2～1.2 d B的增益,综合两者后的重构算法可获得3.8～4.3 d B以上的增益.展开更多
文摘针对农田监测区域大、监测节点能量有限以及异常事件具有偶发性等特点,提出了一种基于改进压缩采样匹配追踪的农田信息异常事件检测算法(DP-CoSaMP)。针对传统压缩采样匹配追踪(Compressive sampling matching pursuit,Co Sa MP)算法中相似原子选择和稀疏度要求已知问题,引进Dice系数有效区分原子相关性,保证选择最优原子;利用峰值信噪比(Peak signal to noise ratio,PSNR)与匹配信号残差具有相似变化趋势,动态调整算法迭代次数,避免稀疏度获取困难问题。仿真实验结果表明,本文算法异常事件检测成功率较现有算法提高了20%,网络能耗降低了15%,平均检测时间减少了50%。
文摘为有效解决压缩采样匹配追踪(compressive sampling matching pursuit,Co Sa MP)算法对稀疏度K值的依赖问题,提高重构精度,提出了一种根据峰值信噪比增减变化趋势来确定最佳迭代次数的Co Sa MP改进算法。先将PSNR算式进行数学推导演变,将算式中未知的原始信号巧妙转换为已知信号,并证明了此转换式与PSNR算式有相同增减性,在迭代过程中基于此转换式可根据各列稀疏度的不同,自适应地确定不同列的最佳迭代次数,从而保证更高的重构精度。理论分析和实验仿真表明,改进的Co Sa MP算法比原有算法有更理想的重构效果,与其他重构算法相比有更高的重构成功率,并且更具高效性和实用性。
基金the Youth Foundation of Jiangxi Provincial Education Department,China
文摘Compressive sampling matching pursuit （CoSaMP） algorithm integrates the idea of combining algorithm to ensure running speed and provides rigorous error bounds which provide a good theoretical guarantee to convergence. And compressive sensing （CS） can help us ease the pressure of hardware facility from the requirements of the huge amount in information processing. Therefore, a new video coding framework was proposed, which was based on CS and curvelet transform in this paper. Firstly, this new framework uses curvelet transform and CS to the key frame of test sequence, and then gains recovery frame via CoSaMP to achieve data compress. In the classic CoSaMP method, the halting criterion is that the number of iterations is fixed. Therefore, a new stopping rule is discussed to halting the algorithm in this paper to obtain better performance. According to a large number of experimental results, we ran see that this new framework has better performance and lower RMSE. Through the analysis of the experimental data, it is found that the selection of number of measurements and sparsity level has great influence on the new framework. So how to select the optimal parameters to gain better performance deserves worthy of further study.
文摘考虑到井下应急救灾的需要,设计了一种基于压缩感知和无线传感器网络(WSNs)的矿井应急语音通信系统。根据语音信号的稀疏性,采用压缩感知的方法,对语音信号进行随机采样并传输,在Sink接收端,分别利用OMP算法和Co Sa MP算法进行信号重构,对比仿真实验表明:Co Sa MP重构效果较好。考虑到井下无线信号传输受限,进行了井下无线通信实验,表明在通信距离为20 m情况下,可实时可靠地实现井下应急语音通信。
文摘提出了一种基于双密度双树复小波(double-density dual-tree complex wavelet transform,DDDT-CWT)基的结构化CS图像重构算法,该算法将图像在双密度双树复小波变换下的系数呈现的树结构化特征与Co Sa MP重构算法相结合,实现了对原始图像的更精确重构.实验结果表明:在相同压缩比的前提下,与传统使用DWT基且未考虑变换系数结构化特征的重构算法相比,使用DDDT-CWT基和融入结构化特征的重构算法分别可获得2.9～3.2 d B与0.2～1.2 d B的增益,综合两者后的重构算法可获得3.8～4.3 d B以上的增益.
