一种求解非线性方程全部实根的算法与实现

本文将模拟退火算法与根的逐步搜索方法相结合,给出了求解非线性方程全部实根近似值的一种算法,在Matlab环境下实现了该算法,通过数值实验证明了该算法的有效性,所求得的根具有较高的精度。     

基于单片机的电网性能参数监测系统设计

为了用电安全,提出一种基于单片机的电网性能参数监测技术设计。系统由硬件和软件两部分组成,硬件采用ATmega16单片机为核心对电网进行峰值、双路电压相位差、频率、高频干扰信号等电量参数进行在线监测,软件了解电网供电实时状况,确保电网的安全可靠运行。仿真结果表明,可对电网参数进行实时监测。系统简单可靠、实现方便。     

一种频域信噪比估计方法

本文介绍一种在频域对接收信号进行信噪比估计的算法,该算法不需要接收信号的先验信息,并且具有计算速度快,在频率偏差较大的情况下仍然有较好的估计效果.     

人类的记忆在衰退吗？

在近期《科学杂志》上发表的一篇研究报告称,电脑和互联网的普及正在改变人类记忆的基本方式。很多人都有这样的经验：当你能用工具将什么东西记录下来时,实际上是在告诉自己的大脑：＂你没有必要记住它。＂     

求非线性最小二乘估计的一种算法

本文利用正交表给出一种求非线性ＬＳＥ良参数初始值的算法—正交搜索法，进而与迭代法结合求解非线性ＬＳＥ，通过求解非线性强度大模型的非线性ＬＳＥ，说明新算法使用灵活、有效     

非英语专业本科生英语学习动机衰退的内因研究

非英语专业本科生中普遍存在英语学习动机衰退的现象。文章通过对某高校非英语专业的120名本科学生的调查研究,探讨了影响学生英语学习动机衰退的内部因素。研究结果表明,英语学能、学习焦虑、兴趣、目标甚至童年的学习经历等是导致学习者英语学习动机衰退的主要内部因素。     

煤炭矿区衰退的机理及可持续发展对策研究

本文首先建立煤炭矿区PREES系统的概念,为矿区衰退机理的研究奠定了基础,运用耗散理论深入探讨了矿区衰退的内在机理,揭示出矿区系统只有形成耗散结构、才能有活力、实现可持续发展.本文最后给出了煤炭矿区实现可持续发展的建议及对策.     

浅谈一种发动机冷却系统水阻测量方法

发动机冷却系统流道复杂,阻力较难计算。本文提出了一种利用水泵性能台架对发动机水阻进行测量的方法,为发动机冷却系统及水泵的设计开发提供基础数据。     

一种基于FPGA的硬件神经网络设计方法

在FPGA硬件神经网络设计中激活函数的实现和数据表示方式是两个难点。本文提出了用非线性函数和21位定点法相结合来实现激活函数的逼近算法,采用源码定点表示法实现数据的硬件表示,明显减少了FPGA的资源占用,降低了激活函数逼近算法的复杂性和实现难度,最后,给出实际FPGA硬件神经网络设计实例并进行了仿真验证。     

Global derivative based sensitivity method for parameter estimation

In nonlinear parameter estimation local sensitivity assessment; conventionally measured by the first-order derivative of the predicted response with respect to a parameter of interest fails to provide a representative picture of the prediction sensitivity in the presence of significant parameter co-dependencies and/or nonlinearities. In this article we derive the profile-based sensitivity measure developed by Sulieman et al. (2001, 2004) [1] and [2] in the context of model re-parameterization. In particular, the so-called predicted response re-parameterization is shown to ultimately lead to the profile-based sensitivity coefficient defined by the total derivative of the model predicted response with respect to a parameter. Although inherently local, the profile-based measure is shown to handle simultaneous perturbations in parameter values while accounting for their co-dependencies. Thus the proposed measure possesses a central property of a global sensitivity measure and so it is considered hybrid local-global measure.The global Fourier amplitude sensitivity test (FAST) is added to the analysis and compared with both marginal and profile-based sensitivity methods. The Fourier sine amplitude is utilized here as a first-order sensitivity measure and shown to be directly linked to the local sensitivity coefficient averaged over all ranges of parameter uncertainties and so it is also considered hybrid local-global measure. The comparisons are explained by three compelling model cases with different degrees of parameter co-dependencies and nonlinearities.     

Recursive parameter estimation algorithm for multivariate output-error systems

In this paper, we consider the parameter estimation issues of a class of multivariate output-error systems. A decomposition based recursive least squares identification method is proposed using the hierarchical identification principle and the auxiliary model idea, and its convergence is analyzed through the stochastic process theory. Compared with the existing results on parameter estimation of multivariate output-error systems, a distinct feature for the proposed algorithm is that such a system is decomposed into several sub-systems with smaller dimensions so that parameters to be identified can be estimated interactively. The analysis shows that the estimation errors converge to zero in mean square under certain conditions. Finally, in order to show the effectiveness of the proposed approach, some numerical simulations are provided.     

Several gradient parameter estimation algorithms for dual-rate sampled systems

This paper presents three identification methods for dual-rate sampled systems. The first method combines the stochastic gradient algorithm with the polynomial transformation technique, which can estimate the parameters of the identification model. The second method is the finite impulse response model based stochastic gradient algorithm, which can indirectly estimate the parameters of the dual-rate systems by using all the inputs and the available outputs. The third method is the missing output estimation model based stochastic gradient algorithm with a forgetting factor, which can directly estimate the parameters of the dual-rate systems by using all the inputs and all the outputs (include the estimated outputs). An example is provided to verify the effectiveness of the proposed methods.     

Analysis and parameter estimation of bilinear systems via Chebyshev polynomials

The operational properties of the integration and product of Chebyshev polynomials are used in the analysis of bilinear systems by the approximation of time functions by truncated Chebyshev series. The operational properties are also applied to determine the unknown parameters of a general bilinear system from the input-output data. Examples with excellent results are given.     

Distributed dynamic state estimation with parameter identification for large-scale systems

In this paper, we consider a distributed dynamic state estimation problem for time-varying systems. Based on the distributed maximum a posteriori (MAP) estimation algorithm proposed in our previous study, which studies the linear measurement models of each subsystem, and by weakening the constraint condition as that each time-varying subsystem is observable, this paper proves that the error covariances of state estimation and prediction obtained from the improved algorithm are respectively positive definite and have upper bounds, which verifies the feasibility of this algorithm. We also use new weighting functions and time-varying exponential smoothing method to ensure the robustness and improve the forecast accuracy of the distributed state estimation method. At last, an example is used to demonstrate the effectiveness of the proposed algorithm together with the parameter identification.     

Hubble parameter estimation via dark sirens with the LISA-Taiji network

The Hubble parameter is one of the central parameters in modern cosmology,and describes the present expansion rate of the universe.The values of the parameter i...