基于二级融合的矿井环境智能监测研究

为保证矿井生产环境安全,以井下数据采集系统为基础,提出了最短距离聚类融合算法,以克服传感器测量误差和系统误差,实现对井下环境信息的数据级融合,与已有文献相比提高了融合精度。在此基础上,设计了概率神经网络分类器对数据级融合结果进行决策级融合,完成了矿井环境安全等级划分,实现了矿井环境安全状态的智能监测。实践表明:此两级融合方法在矿井环境监测系统中是可行的、有效的。     

Programmer-transparent coordination of recovering concurrentprocesses: philosophy and rules for efficient implementation

An approach to coordination of cooperating concurrent processes, each capable of error direction and recovery, is presented. Error detection, rollback, and retry in a process are specified by a well-structured language construct called recovery block. Recovery points of processes must be properly coordinated to prevent a disastrous avalanche of process rollbacks. The approach relies on an intelligent processor system (that runs processes) capable of establishing and discarding the recovery points of interacting processes in a well coordinated manner such that a process never makes two consecutive rollbacks without making a retry between the two, and every process rollback becomes a minimum-distance rollback. Following a discussion of the underlying philosophy of the author's approach, basic rules of reducing storage and time overhead in such a processor system are discussed. Examples are drawn from the systems in which processes communicate through monitors     

伺服系统的复合自适应滑模控制

对于采用自适应方法的鲁棒跟踪控制系统,初始参数估计误差、参数突变、非持续激励等因素均可引起瞬态过程.瞬态性能的好坏对跟踪误差峰值及恢复时间有较大影响,是实现高性能跟踪控制的关键,而目前典型设计多采用直接自适应方法,其较差的瞬态特性制约了跟踪性能的进一步提高.针对该问题,以交流伺服系统为研究对象,将直接自适应、间接自适应及滑模控制相融合,提出一种基于有界增益遗忘最小二乘法的复合自适应滑模控制( CASMC)策略,Lyapunov分析表明该策略可实现持续激励条件下跟踪误差和参数估计误差在较大范围内的指数收敛,瞬态特性较清晰.最后,以某型火炮的方位轴伺服系统为应用背景进行仿真实验,结果显示,该控制策略在瞬态过程的误差峰值和持续时间方面均有显著改善,提高了伺服系统的跟踪性能.     

Luenberger observers for switching discrete-time linear systems

State estimation is considered for a class of switching discrete-time linear systems. The switching is assumed to be unknown among the various system modes associated with different known matrices. The proposed scheme relies on the combination of the estimation of the system mode with the application of a Luenberger-like observer whose gain is a function of the estimated mode. In the absence of noises, the estimate of the mode can be chosen among the ones that are consistent with the measurements and the stability of the estimation error is ensured under suitable conditions on the observer gains. Such conditions can be expressed by means of linear matrix inequalities (LMIs). The presence of bounded disturbances is also taken explicitly into consideration. In this situation, a novel method based on a minimum-distance criterion is proposed in order to estimate the system mode. Also in this case the error of the resulting estimator is proved to be exponentially bounded.     

Sparse recovery based reversible data hiding method using the human visual system

In this paper, a novel sparse recovery based reversible data hiding (RDH) method using the human visual system (HVS) is presented. To improve the low accuracy of existing predictors, a sparse recovery based predictor is proposed. In the processes of sparse recovery, the most relevant neighbors can be adaptively chosen by using sparse representation to predict the current pixel accurately, and thus the concentrated prediction error histogram (PEH) is built to obtain good embedding performance. Moreover, to overcome the conflict between the embedding order of the traditional RDH method and the evaluation of HVS, a new embedding strategy based on just noticeable difference (JND) is designed. In this strategy, pixels are classified into sensitive and in-sensitive clusters according to JND values, and two corresponding PEHs are built. Accordingly, different inner regions of two PEHs are adjusted to meet the required embedding capacity, and the prediction error expansion (PEE) technique is utilized to embed data. Experimental results prove that the proposed method outperforms the state-of-the-art RDH methods, including JND related methods.     

Recovery of Collided RFID Tags With Frequency Drift on Physical Layer

In a passive ultra-high frequency (UHF) radio frequency identification (RFID) system, the recovery of collided tag signals on a physical layer can enhance identification efficiency. However, frequency drift is very common in UHF RFID systems, and will have an influence on the recovery on the physical layer. To address the problem of recovery with the frequency drift, this paper adopts a radial basis function (RBF) network to separate the collision signals, and decode the signals via FM0 to recovery collided RFID tags. Numerical results show that the method in this paper has better performance of symbol error rate (SER) and separation efficiency compared to conventional methods when frequency drift occurs.      

Recovering the missing components in a large noisy low-rank matrix: application to SFM

In computer vision, it is common to require operations on matrices with "missing data," for example, because of occlusion or tracking failures in the Structure from Motion (SFM) problem. Such a problem can be tackled, allowing the recovery of the missing values, if the matrix should be of low rank (when noise free). The filling in of missing values is known as imputation. Imputation can also be applied in the various subspace techniques for face and shape classification, online "recommender" systems, and a wide variety of other applications. However, iterative imputation can lead to the "recovery" of data that is seriously in error. In this paper, we provide a method to recover the most reliable imputation, in terms of deciding when the inclusion of extra rows or columns, containing significant numbers of missing entries, is likely to lead to poor recovery of the missing parts. Although the proposed approach can be equally applied to a wide range of imputation methods, this paper addresses only the SFM problem. The performance of the proposed method is compared with Jacobs' and Shum's methods for SFM.     

立体视频误码恢复技术综述

随着立体视频技术的发展,大量视频数据的传输面临着巨大的挑战。当经过错误信道传输时,视频数据常常面临出错或丢失的现象,因而,有效的误码恢复技术变得极为重要。首先介绍了一些常见的立体视频编码结构及其对应的误码现象,并针对目前已有的立体视频误码恢复技术的编码结构,对相应的误码恢复方法进行了研究和分析。最后,指出了进一步发展的前景。     

超标量处理器中寄存器别名表恢复方法的改进研究

寄存器重命名是超标量处理器用于提升指令集并行度的重要方法,其基本实现方式是通过寄存器别名表来记录逻辑寄存器和物理寄存器的映射关系,当发生分支预测错误时需要对寄存器别名表中的内容进行恢复。针对于现有的恢复方法没有利用重命名的局部性特征,在处理器的指令窗口增加时暴露出实现代价过大的问题,提出了一种基于区间进行寄存器别名表恢复的改进型恢复方法,通过对walk方法的改造,使用区间计分板来确定需要扫描的地址范围,并精确地控制每个区间的扫描,可以大大减小资源浪费。通过对逻辑综合结果和性能进行分析,相比于检查点恢复的传统设计,这种方法使用更少的面积和功耗,达到与检查点方式恢复接近的性能,也具有更好的扩展潜力。     

联合矩阵F范数的低秩图像去噪

摘 要：目的：低秩矩阵恢复是通过最小化矩阵核范数来获得低秩解,然而待恢复低秩矩阵相关性低的要求往往会导致求解不稳定的情况。方法：针对该问题,研究一种基于变量分裂的低秩图像恢复去噪算法,引入待恢复矩阵的Frobenius范数作为新正则项,与原有低秩矩阵的核范数组成联合正则化项,对问题进行凸松弛后,采用变量分裂的增广拉格朗日乘子法求解。结果：为考察方法的稳定性和去噪能力,选取了不同参数类型的加噪图像进行仿真,并结合恢复时间、信噪比、差错率等评价标准与现有低秩矩阵恢复算法进行对比。结论：实验结果表明增加Frobenius范数的低秩矩阵恢复模型在保持原有低秩稀疏恢复的前提下,具有良好的去噪性能,对相关性强的低秩图像恢复结果稳定性好,获得了更高的信噪比。     

基于压缩感知和宽带调制的统一测控信号处理仿真

针对测控信号处理中,在可用频谱上分布着多种频分下行信号的场景,分别利用标准测控信号和扩频测控信号在频域上的绝对稀疏性和相对稀疏性,提出了一种基于压缩感知和宽带调制的低速采样方案.首先通过多通道调制得到低速的采样序列,而为了克服现有信号重构算法重构精度较差的缺点,利用阈值迭代方法从采样序列中重构出原信号,最后对重构后的信号进行解调/解扩处理并进行误码率分析.仿真结果表明,新方案能够在低采样率的条件下获得很好的性能.     

观测误差协方差估计下的集合鲁棒滤波数据同化方法

在数据同化方法中,观测误差协方差矩阵是相关的,且与时间和状态有一定的依赖性。针对这种相关特性,将鲁棒滤波方法与观测误差协方差估计方法相结合,得到随状态时间变化的观测误差协方差,提出一种带有观测误差估计的鲁棒数据同化新方法,更新观测误差协方差,改善估计效果。从分析误差协方差,转移矩阵特征值放大等角度优化同化方法。利用非线性Lorenz-96混沌系统,对三种不同优化角度下带有观测误差估计的鲁棒滤波和原鲁棒滤波方法的鲁棒性和同化精度进行评估,并比较分析了两种方法在模型误差、观测数目和性能水平系数变化时的性能。结果表明：观测误差估计技术能够提高状态估计的精确性,带有观测误差估计的鲁棒滤波对系统参数变化具有较好的鲁棒性。     

File recovery by ISO FTAM

File recovery enhances the reliability and robustness of a network file management system. This capability of error detection and recovery is examined in an FTAM implementation. The issues of docket design, checkpoint insertion, recoverability, as well as interface transparency, are discussed in the paper. The impact of the recovery on the end-to-end performance and the effectiveness of the error recovery protocol in the light of failures are also examined by means of performance measurements. The result shows that the advantage gained by error recovery outweighs the protocol overheads incurred in the process.     

H.264/AVC video error concealment algorithm by employing motion vector recovery under cloud computing environment

Network-based cloud computing has rapidly expanded as an effective way of video processing and transmission. Since packet losses or errors may frequently occur in cloud computing environment during the transmission of compressed video, error concealment is applied in the decoder to prevent significant degradation of image quality. Motion vector (MV) recovery is a widely-used temporal error concealment which shows satisfactory performance in practical application of video transmission. In this paper, a fast and effective temporal error concealment algorithm for H.264/AVC is presented, which efficiently utilizes the MVs of neighboring macroblocks (MB) which are adjacent to the lost MB under different circumstances. To ensure the precision of the MV recovery, a smallest division of \(4\times 4\) sub-block is applied, which will not bring too much complexity in the proposed algorithm. Each MV of sub-block is restored in individual method, and the recovery information is gathered from the nearby 20 sub-blocks. Simulation results under the virtual cloud environment show that our scheme can highly improve the quality of reconstructed video and obtain a gain of about 4 dB in PSNR, compared with other temporal error concealment methods in the condition of different packet loss rates and quantization parameters. The practical simplicity ensures that the proposed method can be readily applied to real-time video applications running under cloud computing environment.     

基于动态参数的函数空间学习最优核映射

核函数方法可挖掘出高精度快速印刷品图像间的非线性分布规律,而挖掘能力由所选择的核函数及其参数来决定。这两者的学习与选择同样是核函数理论继续发展与实际应用需要迫切解决的问题。针对印刷品智能检测这一特定背景,提出了一种新的基于优化问题的从具有动态参数的函数空间中学习核函数及参数的方法,以此来使核函数方法达到最优性能。与传统的计算方法不同之处在于其核函数空间中的核参数是连续变化的,这使学习的范围得到一个维度上的扩展。实验结果显示,结合理论分析的迭代算法仅需要10次迭代便可得到统计最优的核函数及参数,利用学习到的核函数计算的复原误差是统计最小的。     

IP网络MPEG-4视频流的自适应差错掩盖算法

针对IP网络上的MPEG-4视频传输,采用面向差错控制的打包方案,提出了一种结合时域差错恢复和空域差错恢复方法的快速自适应差错恢复混合算法。该算法根据视频帧的编码模式、丢失宏块的邻域宏块的编码模式、运动程度和运动矢量一致性自适应地选择差错恢复方法。仿真实验结果验证了自适应算法具有较好的差错恢复能力。     

块级连续数据保护系统元数据管理方法

为有效组织连续数据保护(CDP)的历史数据以提高灾难发生时系统的恢复效率,研究了影响CDP系统恢复性能的元数据管理方法,设计并实现了三种元数据管理方法。其中两种(DIR-MySQL和OPT-MySQL)是简单的基于MySQL数据库的实现,而另一种(META-CDP)是根据应用特点而设计的。实验结果表明,三种管理方法均能够有效提高系统的恢复效率。其中,前两种方式随着恢复数据量的增加,所需要的恢复时间剧增;而后一种方式随着数据量的增加,恢复时间增加很小,其效率比前两种方法高很多,而且其性能也在可接受范围内。     

An iterative approach for sparse direction-of-arrival estimation in co-prime arrays with off-grid targets

This paper addresses the problem of direction of arrival (DOA) estimation by exploiting the sparsity enforced recovery technique for co-prime arrays, which can increase the degrees of freedom. To apply the sparsity based technique, the discretization of the potential DOA range is required and every target must fall on the predefined grid. Off-grid target can highly deteriorate the recovery performance. To the end, this paper takes the off-grid DOAs into account and reformulates the sparse recovery problem with unknown grid offset vector. By introducing a convex function majorizing the given objective function, an iterative approach is developed to gradually amend the offset vector to achieve final DOA estimation. Numerical simulations are provided to verify the effectiveness of the proposed method in terms of detection ability, resolution ability and root mean squared estimation error, as compared to the other state-of-the-art methods.     

A recognition-based motion capture baseline on the HumanEva II test data

The advent of the HumanEva standardized motion capture data sets has enabled quantitative evaluation of motion capture algorithms on comparable terms. This paper measures the performance of an existing monocular recognition-based pose recovery algorithm on select HumanEva data, including all the HumanEva II clips. The method uses a physically motivated Markov process to connect adjacent frames and achieve a 3D relative mean error of 8.9 cm per joint. It further investigates factors contributing to the error and finds that research into better pose retrieval methods offers promise for improvement of this technique and those related to it. Finally, it investigates the effects of local search optimization with the same recognition-based algorithm and finds no significant deterioration in the results, indicating that processing speed can be largely independent of the size of the recognition library for this approach.     

基于H.263+视频传输的误差恢复技术

论文提出了一种应用于H.263+视频传输的误差恢复方法,即基于H.263+视频编解码器的差错掩盖方法。在这种方法中,在编码器端通过重传出现差错的数据和发送帧内编码帧来限制误差的扩散和繁衍;在解码器端利用视频信号在空间域和时间域上的相关性对受损的数据进行误差掩盖。模拟结果表明,这种误差恢复方法能够使得在有噪音干扰信道上传输的图像质量获得明显改善。其可以应用于公共交换电话网(PSTN)、Internet等能够提供反馈信道的视频通信环境中。