剪板机的PLC控制系统设计

对剪板机的工作原理及控制特点进行了分析，选用F1－40MR型PLC为控制器，设计出剪板机控制系统，包括硬件电路和软件程序。实践结果,该设计方案合理，可靠性高，有很好的实用性。     

Analog VLSI Stochastic Perturbative Learning Architectures

We present analog VLSI neuromorphic architectures fora general class of learning tasks, which include supervised learning,reinforcement learning, and temporal difference learning. Thepresented architectures are parallel, cellular, sparse in globalinterconnects, distributed in representation, and robust to noiseand mismatches in the implementation. They use a parallel stochasticperturbation technique to estimate the effect of weight changeson network outputs, rather than calculating derivatives basedon a model of the network. This model-free technique avoidserrors due to mismatches in the physical implementation of thenetwork, and more generally allows to train networks of whichthe exact characteristics and structure are not known. With additionalmechanisms of reinforcement learning, networks of fairly generalstructure are trained effectively from an arbitrarily suppliedreward signal. No prior assumptions are required on the structureof the network nor on the specifics of the desired network response.     

Preconditioned accelerated generalized successive overrelaxation method for solving complex symmetric linear systems

In this paper, by adopting the preconditioned technique for the accelerated generalized successive overrelaxation method (AGSOR) proposed by Edalatpour et al. (2015), we establish the preconditioned AGSOR (PAGSOR) iteration method for solving a class of complex symmetric linear systems. The convergence conditions, optimal iteration parameters and corresponding optimal convergence factor of the PAGSOR iteration method are determined. Besides, we prove that the spectral radius of the PAGSOR iteration method is smaller than that of the AGSOR one under proper restrictions, and its optimal convergence factor is smaller than that of the preconditioned symmetric block triangular splitting (PSBTS) one put forward by Zhang et al. (2018) recently. The spectral properties of the preconditioned PAGSOR matrix are also proposed. Numerical experiments illustrate the correctness of the theories and the effectiveness of the proposed iteration method and the preconditioner for the generalized minimal residual (GMRES) method.     

基于光谱加权低秩矩阵分解的高光谱影像去噪方法

高光谱遥感影像在获取和传输过程中会受到各种类型噪声的污染,不仅降低影像质量,也限制了其后续应用的精度。高光谱影像噪声类型复杂多样,且噪声在不同波段上的强度也并不相同。通过引入光谱域上的权重矩阵,文中提出了一种基于光谱加权低秩矩阵分解的高光谱遥感影像混合噪声去除方法,利用光谱权重矩阵均衡不同波段的噪声强度差异性。为进一步将噪声与纯净影像分离,利用加权核范数最小化来约束纯净高光谱影像的局部低秩结构,并利用交替方向乘子法对所提出的模型进行优化求解。通过对模拟与真实高光谱遥感数据的实验,验证了所提方法的有效性与优越性。     

高阶逼近Grünwald-Letnikov分数阶加权系数的快速算法

文中提出三种求解高阶逼近任意运算阶的Grünwald-Letnikov分数阶微分器系数的快速算法,表述了算法的实现原理及对应的推导公式,并对其进行运行时间统计和计算复杂度分析。与幂级数展开法、卷积计算法、复化Simpson数值逼近法和IFFT相比,快速算法可以在误差允许的范围内,降低求解Grünwald-Letnikov分数阶微分器系数的计算复杂度,从而提高执行效率。     

Performance analysis of achievable sum‐rate for downlink massive MIMO systems

Massive multiple‐input and multiple‐output (MIMO) has been recognized as a promising technology in the fifth‐generation wireless networks. Under perfect channel state information, we derive three tractable closed‐form expressions that corresponding to the lower bound, approximation, and upper bound on the achievable rate in a massive MIMO downlink system with maximum‐ratio transmission precoding. Based on the proposed closed‐form expressions, the power efficiency of the system is investigated as the number of transmit antennas increases. Simulation results demonstrate the tightness of our proposed closed‐form expressions for the achievable sum‐rate.     

基于稀疏恢复的自适应角度多普勒补偿方法

自适应角度多普勒补偿方法是补偿机载非正侧阵雷达杂波距离相关性的有效手段,该方法解决了角度多普勒补偿方法处理性能受系统误差影响较大的问题,可以实现杂波距离相关性的自适应补偿。但该方法利用子孔径平滑估计杂波协方差矩阵,存在孔径损失,系统自由度下降,估计准确度下降。此外,该方法还存在着运算量大的问题,不利于实时实现。本文提出了一种基于稀疏恢复的自适应角度多普勒补偿方法,并利用正交投影逼近子空间追踪方法对估计杂波协方差矩阵进行特征分解。与常规自适应角度多普勒补偿方法相比,本文方法运算量显著降低,杂波补偿性能更优。理论分析和仿真结果验证了该方法的有效性。     

基于非局部自相似性和低秩矩阵逼近的补全算法

针对传统矩阵补全算法在图像重建方面的不足,提出了一种基于非局部自相似性和低秩矩阵逼近（NL-LRMA）的补全算法。首先,通过相似性度量找到图像中局部块所对应的非局部相似块,并将相应灰度信息进行向量化,从而构建出非局部相似块矩阵;然后,针对所得相似矩阵的低秩性,对其进行低秩补全操作（LRMA）;最后,对补全结果进行重新组合,以达到恢复原始图像的目的。在灰度图像以及RGB图像上进行重建实验,结果表明：在经典数据集上,NL-LRMA算法要比原LRMA算法在平均峰值信噪比（PSNR）上高出4~7 dB;同时,新算法在视觉效果与PSNR值方面也明显优于迭代重加权核范数（IRNN）、加权核范数（WNNM）、LRMA等传统算法。总之,所提算法对传统算法在自然图像重建方面的不足进行了有效弥补,从而为图像重建提供了一种行之有效的解决方案。     

基于时钟树机制的超高速数字锁相放大系统

在超高速数字锁相系统中,虽然可以采用时间交替并行模数转换（Analog-to-digital converter, ADC）结构解决采样速率和采样精度的矛盾,但系统极易受各通道采样时钟抖动的影响。在分析采样时钟抖动与采样有效位数及动态范围关系的基础上,设计了一种基于时钟树机制的并联ADC交替采样结构的超高速数字锁相放大系统。实验结果表明,在相同的测试条件下,该系统比国外主流厂商的商用锁相放大器信噪比提高了约17.5 dB。     

非高斯列维噪声激励下非线性系统的Lyapunov指数

研究了非高斯列维噪声作用下非线性系统的渐近线性化方法和Lyapunov指数.利用渐近线性化方法将非线性系统线性化,通过系统的响应轨迹验证了该方法的有效性.通过广义的伊藤法则公式,推导出了列维噪声驱动下Lyapunov指数的一般表达式.给出当参数变化时,非线性系统的随机稳定性分析.