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71.
Yunong Zhang Ke Chen Hong-Zhou Tan 《Automatic Control, IEEE Transactions on》2009,54(8):1940-1945
This technical note presents theoretical analysis and simulation results on the performance of a classic gradient neural network (GNN), which was designed originally for constant matrix inversion but is now exploited for time-varying matrix inversion. Compared to the constant matrix-inversion case, the gradient neural network inverting a time-varying matrix could only approximately approach its time-varying theoretical inverse, instead of converging exactly. In other words, the steady-state error between the GNN solution and the theoretical/exact inverse does not vanish to zero. In this technical note, the upper bound of such an error is estimated firstly. The global exponential convergence rate is then analyzed for such a Hopfield-type neural network when approaching the bound error. Computer-simulation results finally substantiate the performance analysis of this gradient neural network exploited to invert online time-varying matrices. 相似文献
72.
遥感影像配准中,由于光照、成像角度、几何变形等因素的影响,无论采用何种配准方法,总会产生误匹配点,因此误匹配点检测也是一个非常重要的步骤。针对常用RANSAC (Random Sample Consensus)方法不稳定、无法准确检测分布不均匀匹配点的缺点,提出了分组排序采样一致性(Group Sorted Sample Consensus, GSSAC)方法来提高误匹配点检测的稳定性和精度。分组排序采样方法首先将匹配点分为若干组,在每组内计算匹配点的误差并排序,然后在每组中分别采样若干个匹配点组成估算模型参数需要的匹配点。实验结果表明,GSSAC方法可以稳定的获得高精度的检测结果。 相似文献
73.
Huaitao Shi Jianchang Liu Yuhou Wu Ke Zhang Lixiu Zhang Peng Xue 《International journal of systems science》2016,47(5):1095-1109
It is pretty significant for fault diagnosis timely and accurately to improve the dependability of industrial processes. In this study, fault diagnosis of nonlinear and large-scale processes by variable-weighted kernel Fisher discriminant analysis (KFDA) based on improved biogeography-based optimisation (IBBO) is proposed, referred to as IBBO-KFDA, where IBBO is used to determine the parameters of variable-weighted KFDA, and variable-weighted KFDA is used to solve the multi-classification overlapping problem. The main contributions of this work are four-fold to further improve the performance of KFDA for fault diagnosis. First, a nonlinear fault diagnosis approach with variable-weighted KFDA is developed for maximising separation between the overlapping fault samples. Second, kernel parameters and features selection of variable-weighted KFDA are simultaneously optimised using IBBO. Finally, a single fitness function that combines erroneous diagnosis rate with feature cost is created, a novel mixed kernel function is introduced to improve the classification capability in the feature space and diagnosis accuracy of the IBBO-KFDA, and serves as the target function in the optimisation problem. Moreover, an IBBO approach is developed to obtain the better quality of solution and faster convergence speed. On the one hand, the proposed IBBO-KFDA method is first used on Tennessee Eastman process benchmark data sets to validate the feasibility and efficiency. On the other hand, IBBO-KFDA is applied to diagnose faults of automation gauge control system. Simulation results demonstrate that IBBO-KFDA can obtain better kernel parameters and feature vectors with a lower computing cost, higher diagnosis accuracy and a better real-time capacity. 相似文献
74.
75.
Ke Qin 《Neural Processing Letters》2017,45(1):243-261
The theory of chaos and chaotic neural networks (CNNs) has been widely investigated in the past two decades. However, most researchers in this area have merely focused on how to make full use of CNNs to solve various problems in areas such as pattern recognition, classification, associate memory and cryptography. The philosophy of how to design a CNN is seldom discussed. In this paper, we present a general methodology for designing CNNs. By appropriately choosing a self-feedback mechanism, and also including coupling functions and an external stimulus, we have succeeded in proving that a dynamical system, defined by discrete time feedback equations, does, indeed, possess interesting chaotic properties. To the best of our knowledge, the results presented here are novel and pioneering. 相似文献
76.
Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold. 相似文献
77.
78.
Yang Shuangbao Zhai Zhenhe Xu Ke Wang Zhisen Shi Lingwei Wang Lei Cui Haiying Xu Xiyu 《遥感技术与应用》2017,32(6):1083-1092
The key innovation technology of SAR Altimeter (Synthetic Aperture Radar Altimeter)are Doppler\|beam sharpen and delay/Doppler range compensation.The cooperation of these two technologies makes it has high along track resolution and high precision in height measurement.The ground processor is the key hinge to make sure that SAR altimeter could obtain these superiorities.Many key technologies for SAR altimeter processor,such as Doppler beam\|sharpen,delay/Doppler compensation and the second range correction,multilook,echo model and gradient function for retracker,are introduced in the paper.Based on the processor and related work,some simulation work and airborne experiment were tested by the processor,and both of the quantity results show that the SAR altimeter has more potential superiorities. 相似文献
79.
基于Linux系统通过精细剪裁和优化设计,构建开发了一个Linux多级用户的Ext2二级文件系统,以作GPS等专业嵌入式的文件系统.其系统包括各基本实体(索引节点 、目录节点 、文件节点等)的定义和各功能模块的定义及实现,最后展示了系统部分功能模块的测试数据.本文所构造的Linux文件系统已经过测试并取得了良好效果. 相似文献
80.
为了提高合成孔径雷达(SAR)图像匹配的稳定性和快速性,提出一种改进的SIFT算法。首先使用Canny边缘检测算法代替原算法提取特征点,对SIFT特征向量主方向进行优化,针对SAR图像的相干斑噪声问题,使用一种阈值自适应的Contourlet变换进行噪声抑制,再使用改进的主成分分析算法对提取的特征向量进行降维。与现有方法相比,不但保持了特征的丰富性,而且简化了计算量,提高了运算速度。实验结果表明:改进的SIFT算法能够在SAR图像发生缩放、旋转等变化的情况下进行准确匹配,具有更快的速度和更高的匹配精度。 相似文献