基于小波变换和波形信息的P波检测方法

通过小波变换对ECG信号进行分解 ,根据模极大值对求出所有的P波。之后 ,用一简单有效的方法求出每个P波的起、终点 ,再利用P波的弧度值及P波与折线P波的相关系数值选择出真正的P波。该方法经过MIT BIH心电数据库中 9个长达 30分钟的文件的检验 ,取得了满意的结果。

联合校正源空域信息和时域波形信息的乘性阵列误差校正方法

针对乘性阵列误差(包括幅相误差和互耦)的校正问题,该文依据最大似然准则,提出联合校正源空域信息和时域波形信息的误差校正方法,该方法通过"嵌入式"Newton迭代以及交替迭代实现乘性阵列误差参数的数值优化,具有较快的收敛速度和较高的数值稳健性.此外,文中分别在校正源时域波形信息未知和已知这两种情况下推导乘性阵列误差参数的克拉美罗界.仿真实验验证文中新算法的优越性.

基于全波形信息的混联线路单端行波定位方法

架空线-电缆混联线路,由于各段线路行波波速度不一致,初始行波波头和故障点反射波难以辨识,传统的故障定位算法无法适用。提出了基于全波形信息的故障行波时-频域表现形式;基于故障信号的传播特性和折、反射机理,定性分析了区段内故障和相邻区段故障,行波波形时-频域相似性和差异性,揭示了故障行波全波形与故障点位置一一对应的本质;基于故障行波全波形信息,截取一定时间窗行波信号,对其经连续小波变换得到各频带系数进行时间间隔划分,得到面积相等的时频小块,进而建立故障行波时频谱矩阵,利用波形特征匹配技术,实现混联输电线路准确故障定位。该方法具有清晰的物理意义,无需行波模量波速,无需提取初始行波波头以及后续反射波,可通用于多端混联输电线路。理论研究和大量算例分析结果表明,该方法原理简单,具有较高的实用价值。

基于全波形信息的配网线路故障定位方法研究

针对目前配网单相接地故障定位方法普遍存在的可靠性差、灵敏度低的问题,在分析消弧线圈动作特点和动作时限的基础上,提出了基于全波形信息的配网线路故障定位方法:对于接地故障,通过分析故障相电流在故障发生前及故障发生至消弧线圈动作前的相电流特征,从中提取故障特征量,并采用全过程的波形差动偏移度进行定位。最后通过PSCAD/EMTDC软件仿真,验证了该方法的可行性和可靠性。

故障行波全波形时–频特性分析

基于行波信号的故障检测以故障行波的产生、传输特性和折、反射机理为基础。故障行波是一个宽频带阶跃信号,兼具时域和频域的波形特性。融合故障行波时–频域波形,该文提出基于全波形信息的故障行波表现形式,全面刻画行波的传播过程;深度挖掘故障行波全波形与网络拓扑结构、故障点位置和故障点参数的关联,分析折射和反射过程、传输函数和故障点参数对行波全波形传播造成的影响,对区内各点故障和区内、外故障,行波全波形的相似性和差异性进行了定性分析;运用时–频域波形相关系数实现行波全波形的有效辨识,通过大量PSCAD/EMTDC仿真,总结区内不同故障点,区内、外故障以及不同故障点参数,行波全波形相关系数的变化规律,为基于行波信息的故障检测技术搭建了坚实的理论基础。

联合多元信息的激光雷达点云多核分类方法研究

充分利用激光雷达点云、波形数据和强度图像的特性，提出了一种联合多元信息的激光雷达点云多核学习分类方法。该方法首先提取点云的高程信息、回波的波形信息和强度图像的灰度信息，然后将三者结合形成新的特征数据，最后采用多核学习方法的MKSVM分类器进行分类，并利用国产机载激光雷达获取的数据进行了分类处理实验。实验结果表明：该方法有效地提高了分类的精度。

基于机载全波形LiDAR数据的森林地上生物量估测算法研究

为提高森林地上生物量(AGB)的估测精度,本研究以白桦林为研究对象,以机载全波形激光雷达(Li DAR)数据为研究数据,首先提出了机载全波形Li DAR数据读取与全波形特征信息提取的相关算法,然后结合具体算法的实现提取出每条全波形数据对应的各波形分量的能量信息,进而依据波形能量信息计算出每个样地的全波形激光穿透指数(Fi LPI),之后通过全波形激光穿透指数F i LPI建立其与对应样地实测森林AGB的统计回归模型,同时将森林AGB的估测值与森林AGB的实测值进行对比。结果表明全波形激光穿透指数F i LPI与森林AGB具有很好的相关性(R2为0.885,RMSE为0.095),并且森林AGB的估测值与实测值之间误差的波动较小,提高了森林AGB的估测精度,弥补和提供了机载全波形Li DAR数据估测森林AGB的方法和思路。

心电监护仪屏幕波形提取算法研究

心电监护仪是临床中使用较为广泛的一种心电辅助性诊断监护设备,其准确性直接关系到病人疾病的监护与诊断,但目前对心电监护仪的检定仍停留在人工测定阶段。为实现心电监护仪智能化检定、减少人工测定误差,提出一种心电监护仪屏幕波形提取算法,旨在利用图像处理方式实现智能化提取心电波形并进行监护仪的准确度鉴定。算法采用摄像装置获取心电设备波形屏幕图像,通过传统图像处理技术对其进行去噪、图像校正、剔除小区域等一系列预处理,获取纯净波形图像;再结合预测搜索法提取出数字化波形信息。实验验证表明,该算法提取的波形准确率基本在98%以上,相较于传统算法,在节省人力物力的同时缩小了人工检定阶段的误差,系统还可用于心电图归档、处理,为智能化诊断奠定了基础。

含气条件下提高两相含水率解释精度的方法

大庆油田的开发形势突显了两相流产液剖面分层含水率解释精度的重要性，通过解析两相流递减法的解释模型，给出了两相流测井含气影响的解决办法：只要使用两相流仪器能够不受含气影响并准确测量合层的含水率，采用两相流仪器对在井下实测的产量进行分层解释，就可以大大提高分层含水率的解释精度，解释结果能够满足现场应用的要求；给出了淡水水淹层不受含气影响测准合层含水率的方法；探讨非淡水水淹层普遍适用的测准合层含水率的办法。研究结果对于制定增油降水措施、减少无效水循环、提高采收率具有重要意义。

含噪语音的基音周期提取算法

背景噪声对语音信号的基音周期提取有很大的影响.结合能够对背景噪声进行有效降噪的EMD(Empirical Mode Decomposition)软阈值法,提出了一种噪声背景下语音基音周期提取的方法.首先将EMD软阈值降噪法和中心削波法相结合,对信号进行预处理,然后利用语音信号波形本身的信息,进行波形之间的匹配估计,从而获得准确的语音信号基音周期.仿真实验表明:与传统的基音周期提取方法相比较,所提方法在基音周期提取的准确度方面有很大的提高.

通信化雷达探测技术

随着雷达探测逐步进入强电子对抗、隐身时代,传统雷达体制在战术主动性、能量、数量方面均处于劣势。雷达亟需从探测体制方面进行创新,充分挖掘其合作式探测的主动性、充分利用信号波形的信息维度优势,才能适应未来新型防空作战。该文提出一种新的雷达体制——通信化雷达,其通过在发射信号波形中嵌入发射站动态位置、天线扫描指向、发射时刻等辅助信息,并在接收处理中提取、利用该信息进行目标检测、定位、识别、抗干扰和多目标分辨,可提升远程、隐身、强对抗条件下的雷达探测能力和战场生存力。该文从系统架构、探测原理、性能分析等方面对通信化雷达进行了阐述。

Improved hybrid iterative optimization method for seismic full waveform inversion

In full waveform inversion （FWI）, Hessian information of the misfit function is of vital importance for accelerating the convergence of the inversion; however, it usually is not feasible to directly calculate the Hessian matrix and its inverse. Although the limited memory Broyden-Fletcher-Goldfarb-Shanno （L-BFGS） or Hessian-free inexact Newton （HFN） methods are able to use approximate Hessian information, the information they collect is limited. The two methods can be interlaced because they are able to provide Hessian information for each other; however, the performance of the hybrid iterative method is dependent on the effective switch between the two methods. We have designed a new scheme to realize the dynamic switch between the two methods based on the decrease ratio （DR） of the misfit function （objective function）, and we propose a modified hybrid iterative optimization method. In the new scheme, we compare the DR of the two methods for a given computational cost, and choose the method with a faster DR. Using these steps, the modified method always implements the most efficient method. The results of Marmousi and overthrust model testings indicate that the convergence with our modified method is significantly faster than that in the L-BFGS method with no loss of inversion quality. Moreover, our modified outperforms the enriched method by a little speedup of the convergence. It also exhibits better efficiency than the HFN method.

Reflection full-waveform inversion using a modified phase misfit function

Reflection full-waveform inversion （RFWI） updates the low- and high- wavenumber components, and yields more accurate initial models compared with conventional full-waveform inversion （FWI）. However, there is strong nonlinearity in conventional RFWI because of the lack of low-frequency data and the complexity of the amplitude. The separation of phase and amplitude information makes RFWI more linear. Traditional phase-calculation methods face severe phase wrapping. To solve this problem, we propose a modified phase-calculation method that uses the phase-envelope data to obtain the pseudo phase information. Then, we establish a pseudophase-information-based objective function for RFWI, with the corresponding source and gradient terms. Numerical tests verify that the proposed calculation method using the phase-envelope data guarantees the stability and accuracy of the phase information and the convergence of the objective function. The application on a portion of the Sigsbee2A model and comparison with inversion results of the improved RFWI and conventional FWI methods verify that the pseudophase-based RFWI produces a highly accurate and efficient velocity model. Moreover, the proposed method is robust to noise and high frequency.

Opportunistic Relaying Schemes for Amplify and Forward Bidirectional Relay Channels with Multi antenna Sources

We consider a two-way relay network where the Amplify-and-Forward (AF) protocol is adopted by all relays in this paper.The network consists of two multi-antenna source nodes and multiple distributed single-antenna relays.Two opportunistic relaying schemes are proposed to efficiently utilize the antennas of the source nodes and the relay nodes.In the first scheme,the best relay is selected out by a max-min-max criterion before transmitting.After that,at each source,only the antenna with the largest channel gain between itself and the best relay is activated to transmit and receive signals with full power.In the second scheme,assisted by the best relay which is selected by the typical max-min criterion,both source nodes use all their antennas to exchange data,and match filter beamforming techniques are employed at both source nodes.Further analyses show that all schemes can achieve the full diversity order,and the conclusions are not only mathematically demonstrated but numerically illustrated.System performance comparisons are carried out by numerical methods in terms of rate sum and outage probability,respectively.The beamforming assisted scheme can be found to be superior to the antenna selection scheme when accurate Channel State Information (CSI) is available at the transmitters.Otherwise,the latter is very suitable.

Angle-Threshold Random Beamforming Scheme for Multi-Antenna System

Codebook-based multiple input multiple output(MIMO) beamforming can significantly improve the system spectral efficiency with limited feedback and gets widely adopted.However,this scheme has a drawback of heavy feedback load that the sum feedback rate can be a bottleneck for the communication system,especially when the number of users is large.In this paper,a new scheme using pseudo-random beamforming vectors and angle based threshold in the feedback process is proposed.In the proposed scheme,both the base-station and the users have no need to store a codebook.In each access procedure,the base-station generates a pseudo-random beamforming vector,and each user calculates the angle between the beamforming vectors and its channel state information(CSI) vector.If the angle is less than a predefined angle-threshold,the user feeds back its channel quality indicators(CQI),otherwise it keep silence.Compared with the codebook based scheme,the proposed scheme can largely reduce the sum feedback rate with negligible throughput loss.In particular,when the system has a constraint on the total sum feedback rate in uplink channel,the proposed scheme can increase the system throughput significantly.

Full waveform inversion based on improved MLQN method

Full waveform inversion( FWI) is a challenging data-fitting procedure between model wave field value and theoretical wave field value. The essence of FWI is an optimization problem,and therefore,it is important to study optimization method. The study is based on conventional Memoryless quasi-Newton( MLQN)method. Because the Conjugate Gradient method has ultra linear convergence,the authors propose a method by using Fletcher-Reeves( FR) conjugate gradient information to improve the search direction of the conventional MLQN method. The improved MLQN method not only includes the gradient information and model information,but also contains conjugate gradient information. And it does not increase the amount of calculation during every iterative process. Numerical experiment shows that compared with conventional MLQN method,the improved MLQN method can guarantee the computational efficiency and improve the inversion precision.

Reflection full waveform inversion

Because of the combination of optimization algorithms and full wave equations, full-waveform inversion(FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data.Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.

Adaptive robust beamformer for multi-pair two-way relay networks with imperfect channel state information

In wideband multi-pair two-way relay networks, the performance of beamforming at a relay station(RS) is intimately related to the accuracy of the channel state information(CSI) available. The accuracy of CSI is determined by Doppler spread, delay between beamforming and channel estimation, and density of pilot symbols,including transmit power of pilot symbols. The coefficient of the Gaussian-Markov CSI error model is modeled as a function of CSI delay, Doppler spread, and signal-to-noise ratio, and can be estimated in real time. In accordance with the real-time estimated coefficients of the error model, an adaptive robust maximum signal-to-interferenceand-noise ratio(Max-SINR) plus maximum signal-to-leakage-and-noise ratio(Max-SLNR) beamformer at an RS is proposed to track the variation of the CSI error. From simulation results and analysis, it is shown that: compared to existing non-adaptive beamformers, the proposed adaptive beamformer is more robust and performs much better in the sense of bit error rate(BER); with increase in the density of transmit pilot symbols, its BER and sum-rate performances tend to those of the beamformer of Max-SINR plus Max-SLNR with ideal CSI.