Sea clutter modeling using an autoregressive generalized nonlinear-asymmetric GARCH model

The sea clutter modeling is critical to the radar design and assessment of relevant detection algorithms. In this paper, we investigate a family of generalized autoregressive conditional heteroscedastic (GARCH) processes to model the sea clutter as a time series, in which the current variance is dependent on historical information. The most general model (so-called the ALLGARCH model) provides more flexible variance structures to model non-Gaussian, asymmetry, and nonlinear properties of the clutter. However, after going through the usage of the ALLGARCH model, we find that it is not very suitable because the coefficients of the model, which are numerous, would be difficult to estimate in a real-time operating environment. Meanwhile, we find that some of the coefficients are negligible under almost all kinds of sea environments and weather conditions. Motivated by these observations, we propose a novel GARCH model for sea clutter modeling, which is a generalization of the nonlinear-asymmetric GARCH (NAGARCH) model. Considering the correlation between adjacent clutter returns, autoregressive terms are also introduced. By systematically analyzing practical sea clutter data under different sea environments, we demonstrate that the proposed model achieves comparable fitting effect to some commonly used statistical models. Also, we develop the corresponding generalized likelihood ratio test (GLRT) algorithm for the new model. Numerical simulations exhibit that the proposed detector achieves higher probability of detection, comparing with the AR-GARCH detector.     

Development of PCA-based cluster quantile regression (PCA-CQR) framework for streamflow prediction: Application to the Xiangxi river watershed,China

In this study, a PCA-based cluster quantile regression (PCA-CQR) method was proposed through integrating principal component analysis and quantile regression approaches into a stepwise cluster analysis framework. In detail, the principal component analysis was adopted to overcome the multicollinearity among the explanatory variables, while the quantile regression approach was used to provide probabilistic information in prediction. The proposed PCA-CQR method can effectively capture discrete and nonlinear relationships between explanatory and response variables. The applicability of PCA-CQR was demonstrated by a case study of monthly streamflow prediction in the Xiangxi River, China. The nonlinearity between the hydro-meteorological variables and the streamflow measurements was characterized through the measure of maximal information coefficient (MIC), which demonstrated the need of the proposed PCA-CQR method. The results showed that the previous monthly streamflow and precipitation, as well as potential evapotranspiration in current month posed significant nonlinear impacts on the streamflow in current month. Three components could well reflect the total variance of the input variables. Comparison between traditional SCA and PCA-CQR showed that the proposed approach could provide more accurate predictions than traditional SCA methods. Moreover, probabilistic forecasts could be provided by PCA-CQR, and the 90% predictive intervals could well bracket the observations in both calibration and validation periods. Also, sensitivity analysis was performed to identify the impacts of the control parameters in PCA-CQR on the performance of the proposed model. The results showed the proposed PCA-CQR improved the robustness of traditional SCA. Finally, comparison among PCA-CQR, GRNN and MLR also showed the effectiveness of the proposed method.     

Chirping techniques for enhancing the performance of SOA-based UWB over fiber systems: An experimental demonstration

A phaser-based processing technique was adopted in an UWB over fiber system employing SOA. The target is to simultaneously reduce the ASE noise impact and nonlinear effects inherent to optical amplification. Experimental results prove the effectiveness of chirping in terms of cross correlation and bit error rate.     

单路反馈射频功放预失真线性化方法

该文基于记忆多项式模型,提出一种采用单路反馈的射频功放预失真线性化新方法,只需用正交解调后的IQ信号中的一路,就可完成对预失真器模型参数的获取.该方法可消除使用正交解调器所带来的增益和相位不平衡问题,且节省了一路反馈采样电路,在降低成本、简化设计的同时还能提高预失真线性化的性能.仿真和物理实验结果表明,该文提出的方法是...     

点支式玻璃幕墙索桁架支承体系非线性振动

考虑温度变化及几何非线性影响,采用连续化理论导出点支式玻璃幕墙预应力自平衡索桁架支承体系非线性振动方程。通过Galerkin方法,将偏微分方程转化为常微分方程,并采用Lindstedt-Poincaré(L-P)法对常微分方程进行求解。结合工程实例讨论分析温度变化、振幅、初始张力、矢高等因素对点支式玻璃幕墙预应力自平衡索桁架支承体系非线性振动的影响。算例表明,预应力自平衡索桁架支承体系固有频率随着温度的升高而减小,具有较强的非线性,其自振频率随着振幅发生变化,其非线性振动呈现硬弹簧特性,非线性自振频率高于线性振动频率。     

半挂车用空气弹簧弹性特性分析

利用有限元软件和实验方法对空气弹簧的弹性特性进行研究.在前处理软件Hypermesh建立空气弹簧的模型并对其进行网格划分,采用Abaqus/Standard模块对空气弹簧载荷-位移特性进行仿真计算,并利用台架试验测试空气弹簧的弹性特性.结果表明:空气弹簧具有变刚度特性,能有效提高车辆的行驶平顺性;两种方法结果基本一致,验证了有限元分析模型的正确性,为该类型空气弹簧的设计开发提供了可靠的理论依据.     

Design on a highly birefringent and highly nonlinear tellurite ellipse core photonic crystal fiber with two zero dispersion wavelengths

In this paper, a new photonic crystal fiber (PCF) with two zero dispersion wavelengths (ZDWs) based on the tellurite ellipse core is designed. The air holes in the cladding region have a V-shape distribution, which can increase the birefringence. By adjusting the size of tellurite ellipse core, different birefringence and nonlinearity coefficient can be obtained, and the dispersion can also be tailored. When the long axis of the tellurite ellipse core is 0.5 μm and the short axis is 0.25 μm, the birefringence of 7.66 × 10⁻² and nonlinearity of 3400 W⁻¹ km⁻¹ around 1550 nm are obtained. This PCF structure provides a way to get the high birefringence and nonlinearity at the same time, which can find extensive applications in the optical communication and sensor system.     

On the degree of completeness of cryptographic functions

This paper discusses the degree of completeness of cryptographic functions, which is one of the cryptographic criteria should be considered in the design of stream ciphers. We establish the re- lationships between the degree of completeness and other cryptographic criteria. For resilient Boolean functions, a method to enhance the degree of completeness is proposed, while the nonlinearity and the algebraic degree do not decrease. Moreover, two constructions of resilient functions are provided, which have optimal degree of completeness, high nonlinearity, and high algebraic degree.     

Dynamic electrothermal simulation of integrated resistors at device level

This paper presents the dynamic electrothermal simulation of a rectangular resistor integrated on a semi-conductor substrate. Due to the temperature dependence of the electrical conductivity of the resistive sheet, self-heating provokes a coupling between the electrical and thermal problem and gives rise to nonlinear phenomena. We introduce a time stepping iterative method to perform the calculations. The electrical and thermal solvers are based on FEM and Green's functions techniques, respectively. An extensive dynamic analysis of the device will be presented. The results include heating and cooling curves, Nyquist plot (complex locus) of the thermal impedance, time constant spectrum and structure function. Comparisons with the linear case, i.e. a temperature independent resistor, are made and accompanied by analytical approximations if possible. One key observation is that the nonlinearity may easily be overlooked: its detection is only possible in particular characteristics.     

模糊Smith预估控制在圆锥破碎机控制系统中的应用

针对圆锥破碎机控制系统是一个带有不确定时滞及非线性特性电振给矿机的大纯滞后系统，采用Smith预估控制和模糊控制相结合的串级控制，对系统的主、副回路进行设计，使系统在高性能下运行。