严格反馈非线性系统中参数收敛的系统化方法

研究严格反馈非线性系统中参数的收敛性.在适当的持续激励条件下,通过构造一个显式、全局的强Lyapunov函数,给出了系统参数估计收敛于真值的充分条件,且闭环信号全局一致有界,跟踪误差渐近收敛于零.仿真算例验证了设计方案的可行性和有效性.     

An efficient decision feedback equalizer for the ATSC DTV receiver

In this paper an efficient decision feedback equalizer is presented for the equalization of the received signal in the eight level vestigial sideband, Advanced Television Systems Committee, digital television system, adopting a novel detection rule for symbol detection at the output of the equalizer. The conventional hard limiter is replaced by an efficient symbol detection algorithm, based on the underlying trellis coded modulated coding of the transmitted symbols. The proposed decision device has a marginal computational cost and it can be implemented using simple combinatorial and sequential logic circuitry. When the equalizer operates in the decision directed mode, the normalized least mean squared algorithm is utilized for the adaptation of the equalizer coefficients, in a “stop-and-go” like mode, triggered by a reliability signal associated to the detected symbols. The performance of the proposed method is illustrated by typical computer simulation.     

Efficient sign based normalized adaptive filtering techniques for cancelation of artifacts in ECG signals: Application to wireless biotelemetry

In this paper, several simple and efficient sign based normalized adaptive filters, which are computationally superior having multiplier free weight update loops are used for cancelation of noise in electrocardiographic (ECG) signals. The proposed implementation is suitable for applications such as biotelemetry, where large signal to noise ratios with less computational complexity are required. These schemes mostly employ simple addition, shift operations and achieve considerable speed up over the other least mean square (LMS) based realizations. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal to noise ratio and computational complexity.     

Adaptive finite-time stabilization of uncertain non-autonomous chaotic electromechanical gyrostat systems with unknown parameters

This paper deals with the problem of robust finite-time stabilization of non-autonomous chaotic gyrostat systems. It is assumed that the parameters of the gyrostat system are completely unknown in advance and the system is perturbed by unknown uncertainties and disturbances. Some update laws are proposed to estimate the unknown parameters. Based on the finite-time control idea and the update laws, appropriate control laws are designed to ensure the stabilization of the closed-loop system in a finite time. The finite-time stability and convergence of the closed-loop system are analytically proved. A numerical simulation is given to demonstrate the applicability and robustness of the proposed finite-time controller and to verify the theoretical results.     

五维热传导方程的一族两层显格式

构造了五维热传导方程的一族两层显格式,证明了当截断误差阶为O（τ＋h2）时,其稳定性条件为网比r=hτ2≤21,优于同类的其它显格式,当截断误差阶为O（τ2＋h2）时,可以得到一个简洁而实用的二阶精度的两层显格式.     

分布式网络计算在超声成像系统中的运用

超声成像后期数据处理复杂度高,时效性不足。介绍了一种基于TCP协议和LabVIEW技术的网络分布式计算系统实现方法,充分利用分布广泛的空闲网络计算机资源,在任何时刻,系统能够自适应地管理主从机网络连接、协调已连接的主从机间任务分配、获取从机返回计算结果。以达到更快速地完成超声成像的目的。详细阐述了该系统的实现过程,并通过该方案实现了工件截面的快速成像。与FPGA等通过硬件进行并行计算的方法相比,该方法充分利用现有资源,通过软件功能的增加达到快速计算的目的,降低了系统的成本。     

MEXIT: Maximal un-coupling times for stochastic processes

Classical coupling constructions arrange for copies of the same Markov process started at two different initial states to become equal as soon as possible. In this paper, we consider an alternative coupling framework in which one seeks to arrange for two different Markov (or other stochastic) processes to remain equal for as long as possible, when started in the same state. We refer to this “un-coupling” or “maximal agreement” construction as MEXIT, standing for “maximal exit”. After highlighting the importance of un-coupling arguments in a few key statistical and probabilistic settings, we develop an explicit MEXIT construction for stochastic processes in discrete time with countable state-space. This construction is generalized to random processes on general state-space running in continuous time, and then exemplified by discussion of MEXIT for Brownian motions with two different constant drifts.     

？hrough-Wall Tracking of Human Movers Using Continuous-Wave Radar

An intelligent frequency fitting algorithm is presented for continuous-wave radar to track human movers through walls. With the proper fitting dimension, which is usually determined by the practical detection re- quirements, this technique can improve the localization ac- curacy and the tracking performance without introducing too much calculation burden, and more precisely identify different targets even in the frequency ambiguous areas. This technology can also help to match the estimation re- sults to their corresponding targets automatically, which is of great importance to certain urban sensing applications, such as specific target surveillance and tracking. To further improve the detection performance and better identify the weak targets in the presence of strong noise, CLEAN al- gorithm and adaptive filter technology are also involved. Experimental results are provided to illustrate the algo- rithm performance.     

Low computational complexity family of affine projection algorithms over adaptive distributed incremental networks

This paper presents the problem of distributed estimation in an incremental network based on the family of affine projection (AP) adaptive algorithms. The distributed selective partial update normalized least mean squares (dSPU-NLMS), the distributed SPU-AP algorithm (dSPU-APA), the distributed selective regressor APA (dSR-APA), the distributed dynamic selection of APA (dDS-APA), dSPU-SR-APA and dSPU-DS-APA are introduced in a unified way. These algorithms have low computational complexity feature and close convergence speed to ordinary distributed adaptive algorithms. In dSPU-NLMS and dSPU-APA, the weight coefficients are partially updated at each node during the adaptation. In dSR-APA, the optimum number of input regressors is selected during the weight coefficients update. The dynamic selection of input regressors is used in dDS-APA. dSPU-SR-APA and dSPU-DS-APA combine SPU with SR and DS approaches. In these algorithms, the weight coefficients are partially updated and the input regressors are optimally/dynamically selected at every iteration for each node. In addition, a unified approach for mean-square performance analysis of each individual node is presented. This approach can be used to establish a performance analysis of classical distributed adaptive algorithms as well. The theoretical expressions for stability bounds, transient, and steady-state performance analysis of various distributed APAs are introduced. The validity of the theoretical results and the good performance of dAPAs are demonstrated by several computer simulations.     

Edge preserving adaptive anisotropic diffusion filter approach for the suppression of impulse noise in images

This paper proposes a new anisotropic diffusion approach to remove the impulse noise and retain the fine details. The proposed approach contains two stages, the first stage detects the impulse noise, and the second stage removes the noisy pixel and retains the fine details of the original image. The Laplacian operator is used to fine-tune the image quality of the restored image in the anisotropic diffusion filter. The proposed approach is tested with PSNR, IEF, correlation factor, and NSER for different test images and the results are compared against existing algorithms. The simulation results show that the proposed approach gives better results than the existing denoising algorithms.