混沌的模糊神经网络逆系统控制

提出用Sugeno型的模糊推理神经网络建立混沌系统的逆系统模型,并采用逆系统方法进行混沌的控制.这种方法的特点是可以不必建立混沌系统的解析模型,通过模糊神经网络学习混沌系统的运动规律,通过学习获得的规律对混沌进行有效的控制,并且该控制方法可以控制混沌系统以一定精度跟踪连续变化的给定信号.理论分析及针对虫口模型和Henon模型仿真研究证明了该方法的有效性 关键词： 混沌 模糊神经网络 逆系统控制     

A complex target terrain SAR raw data generation and evaluation based on inversed equalized hybrid-domain algorithm processing

In this paper, synthetic aperture radar raw data generation of complex target terrain based on inverse equalized hybrid-domain processing technique is proposed. Firstly, the basic synthetic aperture radar (SAR) echo model is derived via spectral analysis of extended chirp scaling. Then, the inverse equalized extended chirp scaling algorithm (ECSA) procedure is applied directly step by step to a real input SAR image in order to generate the raw data of the reference SAR image. The whole raw data generation (RDG) procedure only consists of Inverse Equalized ECSA (IEECSA) without integral equation and computation complexity, which means easier implementation and higher efficiency. By applying the resulted RDG into different image formation algorithms (IFAs), not only the final images are reconstructed but also the resulted RDG is evaluated in practice. Finally, valid image quality assessment techniques are implemented on the reconstructed images. The simulations not only confirm the validity of the proposed RDG method based on inverse equalized hybrid-domain technique but also evaluate the quality metrics of reconstructed images as a method of reliability assurance.     

利用凹槽滤波引导混沌系统到周期解

通过对混沌动力系统增加一个线性的反馈控制器——凹槽滤波器,引导一大类系统从混沌运动转化为期望的低周期运动.基于混沌的微扰判据——Melnikov方法,解释了该方法实现混沌控制的数学物理机理.控制仿真结果表明,该方法简单而实用,具有良好的应用前景,并能控制超混沌系统 关键词： 混沌控制 凹槽滤波 Melnikov方法     

供热负荷时间序列混沌特性分析及预报模型研究

为揭示供热负荷时间序列蕴含的内在动态特性,采用非线性分析方法对供热负荷时间序列混沌特性进行识别.以集中供热热源和热力站负荷时间序列为研究对象,进行相空间重构,求得了饱和关联维数和最大Lyapunov指数,验证了供热负荷时间序列的混沌特性,为供热负荷预报研究提供了混沌理论基础.针对现有供热负荷预报方法多为主观模型方法,本文提出了一种基于Volterra自适应滤波器的供热负荷预报方法,该方法不必事先建立主观模型,而直接根据负荷序列本身的特性进行预报,避免了负荷预报的人为主观性.最后,给出了供热负荷预报算例,仿真结果表明二阶Volterra自适应滤波器模型预报精度较高,可满足供热工程节能控制及热力调度的需要. 关键词： 供热节能 负荷预报 混沌 Volterra自适应滤波器     

Noise can prevent onset of chaos in spatiotemporal population dynamics

Many theoretical approaches predict the dynamics of interacting populations to be chaotic but that has very rarely been observed in ecological data. It has therefore risen a question about factors that can prevent the onset of chaos by, for instance, making the population fluctuations synchronized over the whole habitat. One such factor is stochasticity. The so-called Moran effect predicts that a spatially correlated noise can synchronize the local population dynamics in a spatially discrete system, thus preventing the onset of spatiotemporal chaos. On the whole, however, the issue of noise has remained controversial and insufficiently understood. In particular, a well-built nonspatial theory infers that noise enhances chaos by making the system more sensitive to the initial conditions. In this paper, we address the problem of the interplay between deterministic dynamics and noise by considering a spatially explicit predator-prey system where some parameters are affected by noise. Our findings are rather counter-intuitive. We show that a small noise (i.e. preserving the deterministic skeleton) can indeed synchronize the population oscillations throughout space and hence keep the dynamics regular, but the dependence of the chaos prevention probability on the noise intensity is of resonance type. Once chaos has developed, it appears to be stable with respect to a small noise but it can be suppressed by a large noise. Finally, we show that our results are in a good qualitative agreement with some available field data.     

Theoretical and experimental study of Chen chaotic system with notch filter feedback control

Since the past two decades, the time delay feedback control method has attracted more and more attention in chaos control studies because of its simplicity and efficiency compared with other chaos control schemes. Recently, it has been proposed to suppress low-dimensional chaos with the notch filter feedback control method, which can be implemented in a laser system. In this work, we have analytically determined the controllable conditions for notch filter feedback controlling of Chen chaotic system in terms of the Hopf bifurcation theory. The conditions for notch filter feedback controlled Chen chaoitc system having a stable limit cycle solution are given. Meanwhile, we also analysed the Hopf bifurcation direction, which is very important for parameter settings in notch filter feedback control applications. Finally, we apply the notch filter feedback control methods to the electronic circuit experiments and numerical simulations based on the theoretical analysis. The controlling results of notch filter feedback control method well prove the feasibility and reliability of the theoretical analysis.     

Iterative inverse beamforming algorithm and its application in multiple targets detection of passive sonar

With the increasing of detection ability of passive sonar,the weak signal detection problem in multiple interferences becomes more and more important.In the time/bearing record(TBR) display of sonar detection,when there exist traces of multiple interferences,the identification of weak signal is difficult or impossible.The adaptive noise cancellation technique provides the theoretical basis for suppressing strong interferences.But the solution for finding the steady-state optimum filter matrix is quite difficult due to the real time calculation of inverse matrix of input data correlation matrix.The iterative inverse beamforming(IBF) algorithm for solving the optimum filter vector,which is expressed by inverse matrix of the ocean environment data,is derived in this paper,by which,the optimum filter can be eventually expressed as a sum of series simple matrices of constructed from sensor data.Based on the algorithm proposed in this paper,some examples of at sea experiment are provided.The strong interferences are cancelled and the weak signal is emerged,even it didn't appear in the conventional beamforming(CBF) processing.     

Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

In marine radar target detection, sea clutter will cause a large number of missed alarms and false alarms, which will affect the accuracy of target detection. In order to suppress sea clutter effectively, a sea clutter suppression and target detection algorithm of marine radar image sequence based on spatio-temporal domain joint filtering is proposed in this paper. The proposed method is to add a sea clutter suppression link before detecting the target. Firstly, the marine radar image sequence is transformed into three-dimensional frequency wavenumber domain by three-dimensional fast Fourier transform (3D-FFT), and then the three-dimensional image spectrum is obtained. According to the fact that the sea clutter spectrum obtained from the image spectrum satisfies the dispersion relation of linear wave theory in the three-dimensional frequency wavenumber domain, a sea clutter model is established. Then, through the established sea clutter model, a spatio-temporal domain joint sea clutter suppressor is designed to filter the image spectrum. After that, the filtered image spectrum is transformed by three-dimensional inverse fast Fourier transform (3D-IFFT) to obtain the image sequence in which sea clutter is suppressed. Finally, target detection is carried out for sea clutter suppressed image sequence. The method is validated by using the real data of X-band marine radar. Compared with the classical Empirical mode decomposition (EMD) method, the improvement of signal-to-noise ratio (SNR) is more obvious, and SNR can be increased by 15.3 db at most. In addition, compared with target detection on original images directly, the proposed method has excellent detection rate and can increase detection rates by at least 8%.     

0.14 THz高分辨力成像雷达信号处理

为适应0.14 THz超高分辨雷达实时成像的需求,开发了基于CPU+GPU+FPGA的硬件架构和成像处理算法,算法以距离-多普勒为原型,引入L类维格纳分布变换提高横向分辨力,用Keystone变换方法对越距离单元徙动进行校正,并开发了系统非线性补偿算法。在载频0.14 THz、带宽5 GHz雷达样机上进行了逆合成孔径雷达成像试验,获得了3 cm3 cm的成像分辨力和实时成像能力,验证了信号处理方法的有效性。     

DC-DC buck变换器时间延迟反馈混沌化控制

混沌化或反混沌控制是混沌控制的逆问题，通过研究DC-DC buck变换器反混沌控制，为其应用打下理论基础.建立了电压时间延迟反馈buck变换器混沌化控制模型，探讨了它的控制机理，分析了buck变换器混沌化条件和稳定特性，由此仿真研究了不同控制参数对变换器混沌化控制的影响.实验结果表明，该方法控制范围宽，易于实现，是一种较好的反混沌控制方法. 关键词： buck变换器 混沌化 时间延迟反馈控制     

0.14 THz高分辨力成像雷达信号处理

为适应0.14 THz超高分辨雷达实时成像的需求,开发了基于CPU+GPU+FPGA的硬件架构和成像处理算法,算法以距离-多普勒为原型,引入L类维格纳分布变换提高横向分辨力,用Keystone变换方法对越距离单元徙动进行校正,并开发了系统非线性补偿算法。在载频0.14 THz、带宽5 GHz雷达样机上进行了逆合成孔径雷达成像试验,获得了3 cm3 cm的成像分辨力和实时成像能力,验证了信号处理方法的有效性。     

基于自适应随机共振理论的太赫兹雷达信号检测方法

太赫兹雷达系统在差频信号频谱分析过程中,干扰噪声影响其测距能力.针对上述问题,提出基于自适应随机共振理论的太赫兹雷达信号检测方法,通过对含噪差频信号进行二次采样,利用自适应随机共振系统提取信号,进行尺度恢复完成测距计算.实验数据显示,不同测量距离时,相较于快速傅里叶变换法,输出信噪比的平均增益为9.684 d B,其中测量距离为1000 mm处,差频信号初始频谱值提高了64.1倍,系统信噪比增益为11.761 d B;相较于滤波法,在测量距离为1000 mm处信噪比增益最大,提高了70.56%;输入噪声强度为1—5 V之间时,输出信噪比曲线的曲率相对于滤波法降低了86.5%,其中噪声强度为5 V时信噪比增益最大,为14.018 d B.实验表明太赫兹雷达系统的测距能力大幅提高.     

全息滤波光学图像相减

基于傅里叶光学二次滤波技术,本文提出了一种新的光学图像相减方法,即全息滤波光学图像相减法,该方法需用图像的逆转和匹配两种滤波器和一个8f光学系统,实验表明,作为一种新的图像相减方法,避免了以往实时法对光程的精细控制,因而降低了对辅助设备和环境的要求.     

A generalized polynomial chaos based ensemble Kalman filter with high accuracy

As one of the most adopted sequential data assimilation methods in many areas, especially those involving complex nonlinear dynamics, the ensemble Kalman filter (EnKF) has been under extensive investigation regarding its properties and efficiency. Compared to other variants of the Kalman filter (KF), EnKF is straightforward to implement, as it employs random ensembles to represent solution states. This, however, introduces sampling errors that affect the accuracy of EnKF in a negative manner. Though sampling errors can be easily reduced by using a large number of samples, in practice this is undesirable as each ensemble member is a solution of the system of state equations and can be time consuming to compute for large-scale problems. In this paper we present an efficient EnKF implementation via generalized polynomial chaos (gPC) expansion. The key ingredients of the proposed approach involve (1) solving the system of stochastic state equations via the gPC methodology to gain efficiency; and (2) sampling the gPC approximation of the stochastic solution with an arbitrarily large number of samples, at virtually no additional computational cost, to drastically reduce the sampling errors. The resulting algorithm thus achieves a high accuracy at reduced computational cost, compared to the classical implementations of EnKF. Numerical examples are provided to verify the convergence property and accuracy improvement of the new algorithm. We also prove that for linear systems with Gaussian noise, the first-order gPC Kalman filter method is equivalent to the exact Kalman filter.     

Look-up table and Gaussian filter-based inverse halftoning method excellent in gray-scale reproducibility of details and flat regions

Halftoning is a technique in which gray-scale images are converted into binary ones, and has been used widely in many practical image processing applications. On the other hand, inverse halftoning is a technique of reproducing a grayscale image from a binary one. One of the sophisticated inverse halftoning methods which can yield a high quality grayscale image is that based on a look-up table (LUT). In this paper, a new inverse halftoning method based on a combination of this LUT method and a Gaussian filter is discussed. Here, the output gray-scale image is reproduced by blending the output of the LUT-based inverse halftoning and that of the Gaussian filtering appropriately in accordance with local statistics of the image. The effectiveness and the validity of the described method are verified through experiments.     

声管中的宽带脉冲法的水声材料吸声系数测量

现有的水声管吸声系数测量的脉冲法,由于水声管高度的限制,存在低频限制。提出了基于\     

短时交通流复杂动力学特性分析及预测

为揭示短时交通流的内在动态特性,利用非线性方法对交通流混沌特性进行识别,为短时交通流的预测提供基础.基于混沌理论对交通流时间序列进行相空间重构,利用C-C算法计算时间延迟和嵌入维数,采用Grassberger-Procaccia算法计算吸引子关联维数,通过改进小数据量法计算最大Lyapunov指数来判别交通流时间序列的混沌特性.针对局域自适应预测方法在交通流多步预测中预测器系数无法调节的问题,提出了交通流多步自适应预测方法.通过实测数据计算,结果表明:2,4和5 min三种统计尺度的交通流时间序列均具有混沌特性;改进的小数据量法能够准确地计算出最大Lyapunov指数;构建的交通流多步自适应预测模型能够有效地预测交通流量的变化.为智能交通系统诱导和控制提供了依据.     

Optical-feedback induced chaos and its control in semiconductor lasers based on sliding tunable dual-wedges

We present a method of chaos and its control in semiconductor laser based on sliding tunable dual-wedges. We numerically reveal the dynamics of chaos and its control in semiconductor lasers by changing the length of sliding tuneable dual-wedges. The results indicated that, with the appropriate changes of the length of sliding tuneable dual-wedge, the laser can be controlled into steady state, single-periodic, multi-periodic and even chaos respectively. The results also provide a new method to generate various period states in the chaos system.