变宽度凸组合变阶数LMS自适应滤波算法

为了进一步改善凸组合变阶数最小均方(convex combination variable fractional tap-length least mean square,CFTLMS)自适应滤波算法的稳态性能,在证明其稳态性能的基础上,提出了一种变宽度凸组合变阶数(variable width-CFTLMS, VW-CFTLMS)自适应滤波算法,并给出参数的选择依据。仿真结果验证了低信噪比情况下,VW-CFTLMS算法稳态性能和参数选择依据的正确性;同时该算法的稳态性能要优于CFTLMS算法,其额外均方误差相比于CFTLMS算法降低约1.8 dB,具有实用价值。     

Novel reference range selection method in InlSAR imaging

Aiming at the reference range selection for different antennas in interferometric inverse synthetic aperture radar (InISAR) systems, this paper proposes a respective focusing (RF) method. The reference ranges for echoes of different antennas are selected respectively for RF, which is different from the traditional uniform focusing (UF) with the same reference range applied to all the antennas. First, a comparison between UF and RF for InISAR signal model considering the ranging error is given. Compared with RF, UF has an advantage in overcoming the ranging error differences between different antennas. Then the influence of ranging error upon the interferometric imaging with RF is investigated particularly, and it is found that the ranging error differences between different antennas are far smaller than the wavelength, which is advantageous to imaging. By comparing the capabilities of interferometric imaging between RF and UF, it is concluded that RF is a better choice in conquering problems such as image mismatching and phase ambiguity even with ranging errors. Simulations demonstrate the validity of the proposed method.     

Improved adaptive pruning algorithm for least squares support vector regression

As the solutions of the least squares support vector regression machine(LS-SVRM) are not sparse,it leads to slow prediction speed and limits its applications.The defects of the existing adaptive pruning algorithm for LS-SVRM are that the training speed is slow,and the generalization performance is not satisfactory,especially for large scale problems.Hence an improved algorithm is proposed.In order to accelerate the training speed,the pruned data point and fast leave-one-out error are employed to validate the temporary model obtained after decremental learning.The novel objective function in the termination condition which involves the whole constraints generated by all training data points and three pruning strategies are employed to improve the generalization performance.The effectiveness of the proposed algorithm is tested on six benchmark datasets.The sparse LS-SVRM model has a faster training speed and better generalization performance.     

一种改进的H.264/AVC空时编码方案及仿真实现

传统H.264无线视频传输系统误码率较高并且重建图像质量差,针对此问题提出一种改进方案。传输系统采用H.264编码器和多输入多输出(MIMO:Multiple-input Multiple-output)系统级联的模型:基于不等差错保护思想,在信源端依照优先级顺序将H.264码流分为两部分,利用空时预编码技术的分集优势提升高优先级码流的传输可靠性,同时不改变低优先级码流的误码率,提高了无线传输系统整体性能。仿真结果表明:与传统方案相比,改进方案可以在不提高总发送功率的前提下获得较好的重建图像质量,在低信噪比时,重建图像的平均峰值信噪比可提升近7dB,且检测复杂度适中。     

基于RBF的机械手建模误差补偿自适应控制

针对机械手动力学建模误差,提出了基于RBF神经网络误差补偿的自适应控制策略。在基于逆动力学的计算力矩控制方法的基础上,对系统输入与目标轨迹进行修正,设计了两种误差补偿自适应控制器。利用RBF神经网络对修正项在线自学习,并根据Lyapunov稳定性理论建立了网络权重自适应学习律,保证了跟踪误差的收敛及系统的稳定。以平面转动双臂机械手轨迹跟踪为例进行仿真,结果表明该方法能够有效地补偿建模误差,提高了系统的控制性能并使控制系统具有对参数摄动的鲁棒性,对于机械手自适应控制具有一定的可行性。     

带弱奇异核非线性积分微分方程的收敛性分析

利用双线性元对一类带弱奇异核非线性积分微分方程进行了研究。 利用单元已有的高精度分析结果、借助投影算子和平均值技巧, 在各向异性网格下得到了比以往文献高一阶的L²-模最优误差估计。     

粒子群算法修正测距的无线传感器网络节点定位

为获得理想的节点定位结果, 设计一种基于粒子群修正测距的无线传感器节点定位算法. 首先对经典无线传感器节点定位算法DV-Hop的工作原理进行分析, 找到导致测距误差的因素; 然后用粒子群算法对无线传感器节点之间的测距进行修正, 以减少节点间的测距误差, 并对标准粒子群算法的不足进行相应的改进; 最后通过仿真实验与当前经典无线传感器节点定位算法进行对比测试. 测试结果表明, 在相同工作环境下, 该算法提高了无线传感器节点的定位精度, 且未增加额外硬件开销.     

采用质量差和超小导程/直径比丝杠传动的点胶量精细计量技术及系统设计(英文)

基于冗余技术原理,采用制件点胶前后质量差和超小导程/直径比阿基米德丝杠技术组合,辅以自润滑双导轨设计,保证点胶量控制胶滴为(0.200±0.001)g;采用模块化设计,实现点胶机性能的高精度和功能的适度柔性,并通过模块化试制模拟样机,优化点胶机的空间结构及整机可靠性.研究结果表明:该方案保证了点胶量的实时精密控制且同时满足生产节拍的要求.     

求解时变线性不等式离散算法的设计与分析

提出一种用于求解时变线性不等式的数值算法.通过引入一个时变向量(其每个元素都大于或等于零),将时变线性不等式转化为一个时变矩阵向量方程,并给出用于求解该方程的连续时间模型(即神经网络).采用欧拉差分公式将其离散化,推导得到相应的离散算法,并通过理论分析和数值实验验证该离散算法的有效性.结果表明:所提出的离散算法的稳态误差(SSRE)具有O(τ²)的变化规律,当τ的数值减小10倍,算法的稳态误差可减小100倍.     

可压多孔介质流的扩展混合元解法

讨论多孔介质中两种可压缩流体混溶驱动问题数值方法,假定介质是各向异性的,渗透率系数为张量形式。压力方程采用扩展混合元方法求解压力变量、梯度变量,以及速度变量;浓度方程采用标准有限元方法求解,这一方法对各向异性渗透率多孔介质流可以获得更可靠的数值解。构造了半离散数值格式,通过理论分析得到了压力、速度以及浓度等变量的最优L2模误差估计,对浓度变量获得了H1模最优误差估计。