像素聚类改进二进制描述子鲁棒性

目标：本文通过挖掘图像局部区域特征信息,提出了一种鲁棒性更高的二进制描述子。针对BRIEF关于旋转和视角变化鲁棒性差的问题,本文通过图像补丁分层处理、增加关键点图像补丁个数来捕获更多的局部特征信息,对BRIEF描述子改进。方法：首先,根据灰度序列对补丁内所有像素点分类,像素的一个聚类形成了一个亚补丁,然后在每个亚图像补丁上进行类似BRIEF的随机测试。其次,由于原图像补丁大小、尺度大小影响补丁的像素点成分,从而影响像素聚类的效果,所以在原图像关键点周围分割出多个不同大小的图像补丁,或是将原图像补丁根据尺度金字塔确定几个尺度大小不同的补丁,然后再对图像补丁进行分层、测试。所构建的描述子不仅包含了补丁像素的灰度比较信息,而且包含了灰度排序信息和像素群聚信息,提高了描述子的鲁棒性。结果：通过性能对比实验,发现所提的描述子的性能提高了,而且好于对比的浮点描述子。结论：所以挖掘图像补丁的特征信息能提高二进制描述子的鲁棒性。     

混沌和超混沌系统的自适应有限时间投影同步

在混沌系统投影同步的研究中,针对驱动-响应系统达到投影同步的时间不确定问题,提出了一种可以预先计算出同步时间,且在此时间内混沌系统实现投影同步的方法.对给定的驱动系统,构造合适的响应系统;采用自适应控制法,仅在误差系统的部分状态变量上加入自适应控制器;采用李亚普诺夫稳定性理论证明了在所采用的自适应控制律作用下,误差系统稳定同时驱动-响应系统达到有限时间投影同步.以典型的统一混沌系统和超混沌系统进行了数值仿真,结果进一步验证了上述控制方法的有效性与可行性.     

Local adaptive segmentation algorithm for 3-D medical image based on robust feature statistics

Medical image segmentation is of pivotal importance in computer-aided clinical diagnosis. Many factors, including noises, bias field effect, local volume effect, as well as tissue movement may affect the med- ical image, thus causing blurring or uneven characteristics when forming a picture. Such quality defects will inevitably impair the gray-scale difference between adjacent tissues and lead to insufficient segmentation or even leakage during tissue or organ segmentation. In the present investigation, a local adaptive segmentation algorithm for 3-D medical image based on robust feature statistics （LARFS） was proposed. By combining segmentation algorithm principles for traditional region growing （RG） and robust feature statistics （RFS）, the location and neighborhood image information of input seed point can be comprehensively analyzed by LARFS. Results show that, for different segmentation objects, under controlling the input parameter of growing factor within certain range, LARFS segmentation algorithm can adapt well to the regional geometric shape. And be- cause the robust feature statistics is applied in the contour evolution process, LARFS algorithm is not sensitive to noises and not easily influenced by image contrast and object topology. Hence, the leakage and excessive segmentation effects are ameliorated with a smooth edge, and the accuracy can be controlled within the effective error range.     

Guaranteed transient performance based control with input saturation for near space vehicles

This paper describes the design of guaranteed transient performance based attitude control for the near space vehicle(NSV)with control input saturation using the backstepping method.To improve the robust controllability of the NSV,the parameter adaptive method is used to tackle the integrated effect of unknown time-varying disturbance and control input saturation.Based on the backstepping technique and parameter estimated outputs,a robust attitude control scheme is proposed for the NSV with input saturation.A novel robust attitude control scheme is then proposed based on a prescribed performance bound(PPB)which characterizes the convergence rate and maximum overshoot of the attitude tracking error.The closed-loop system stability under both the developed robust attitude control schemes is proved using Lyapunov’s method and uniformly asymptotical convergence of all closed-loop signals is guaranteed.Finally,simulation results are given to show the effectiveness of both the proposed robust constrained attitude control schemes.     

Guaranteeing performance for uncertain nonlinear systems with bounded state constraint and mismatching condition

The control design problem for the uncertain nonlinear system with bounded state constraint and mismatching condition is considered in this paper. The uncertainty in the system, which may be due to unknown system parameters and external disturbance, is nonlinear and time‐varying. The state of the system is constrained to be bounded. The system does not satisfy the (global) matching condition. A creative one‐to‐one state transformation is proposed by converting the bounded states into the unbounded ones. A step‐by‐step state transformation is proposed to convert the mismatched system into a matched system. The robust control is then proposed based on the transformed system. The control is demonstrated to be able to guarantee the uniform boundedness and uniform ultimate boundedness of the system in the presence of uncertainty, while the state constraint can be always guaranteed.     

Observer‐based compensation control of servo systems with backlash

For compensating backlash phenomenon in servo systems, the authors propose an observer method in this paper to estimate both system states and vibration torque before controller design. First, a systematic scheme is given to obtain plant parameters, which is very important in observing system states. This is a parameter estimation principle that gives a crude estimation and computes the differences between the crude and true values. As a result, the precise value of the parameters is obtained by adding together the crude value and the difference. Then, based on the precise estimated parameters, an extended state observer (ESO) is designed to obtain feedback and feedforward signals. Consequently, robust compensation control is achieved by designing an output feedback controller, consisting of a feedback term and a feedforward term. Finally, in order to validate the proposed approach, extensive experiments are performed on a practical servo system with backlash nonlinearity.     

Fixed‐time synchronization for complex‐valued BAM neural networks with time delays

In this paper, the fixed‐time synchronization for complex‐valued bidirectional associative memory (BAM) neural networks with time delays is studied. Based on the fixed‐time stability, the Lyapunov functional method and some inequality techniques, a new criterion is presented to guarantee that the addressed systems achieve synchronization in fixed time and a more accurate estimation independent of the initial conditions is given for the settling time. Meanwhile, a new nonlinear delayed controller different from the existing ones is designed. In the end, two numerical examples are provided to illustrate the effectiveness of the obtained result.     

基于稳健设计的SGNS算法的超参数调优方法

通常给定超参数的若干取值选取性能最大的为最优组合(称为直接选优法),但是此方法的稳健性差。为此,提出了一种基于稳健设计的超参数调优方法(称为稳健调优法)。具体地,以SGNS算法中的超参数调优为例,在词语推断任务上实验并得出:经方差分析得到SGNS算法中的七个超参数中的五个对算法预测性能有显著影响,确定为主控因子,其余两个确定为噪声因子,且主控因子中有三个对性能估计的方差有显著影响,因此,调优中仅从期望最大来直接选优是不合理的;稳健调优法与直接选优法两者在预测性能上没有显著差异,但稳健调优法对噪声因子具有较好的稳健性。稳健调优法对一般的深度神经网络的调参有实际的借鉴意义。     

扩展BVP振子弱周期扰动下的振荡与同步

针对扩展bonhoeffer-van der pol(BVP)振子易受不确定因素影响的问题,提出了将非线性动力学分析与数值模拟相结合的方法,并考察了弱扰动对混合模式振荡类型和同步行为的影响.根据模拟结果得知,多种类型的混合模式振荡受弱扰动的影响出现了坍塌现象,且从理论上证明了两个耦合bonhoeffer-van der pol振子的膜电压比慢变量到达完全同步时所需的耦合强度要大,在二维参数平面上,膜电压到达同步时所取参数范围应小些.结果表明,与膜电压相比,慢变量更容易达到同步,且变量之间呈现一种线性关系.     

基于改进等效电流量测变换的状态估计算法

介绍了基于等效电流量测变换的状态估计算法,并在此基础上提出了一种改进算法.应用抗差估计的理论构造了一组权函数,在每次迭代的过程中对权重不断修改,从而达到提高估计精度的目的.Matlab仿真实验结果表明,估计精度得到了提高.