基于径向基函数神经网络的Lorenz混沌系统滑模控制

针对受参数不确定和外扰影响的混沌Lorenz系统，提出一种基于径向基函数（RBF）神经网 络的滑模控制方法.基于被控系统在不稳定平衡点处状态误差的可控规范形，设计滑模切换 面并将其作为神经网络的唯一输入.单入单出形式的RBF控制器隐层只需7个径向基函数，网 络的权值则依滑模趋近条件在线确定.仿真表明该控制器对系统参数突变和外部干扰具有鲁棒性，同时抑制了抖振. 关键词： 混沌控制 滑模 径向基函数神经网络 Lorenz系统     

神经网络的函数逼近能力分析

本文综述了多层前传网络（ＭＬＰ）及径向基函数网络（ＲＢＦ）对函数任意精度逼近的能力，比较了两种网络的最佳逼近特性。对激活函数类的扩充作了介绍，并说明有限数值精度对函数逼近能力实现的影响。     

五分类血液分析仪的智能光学系统设计

目前国内血液分析仪的白细胞五分类大多以硬件方式实现,且存在硬件结构复杂,制作成本高和过度依赖某些精密部件等问题。为简化五分类仪器的系统结构,提出了一种用于白细胞五分类的智能光学系统,该系统以全光学技术作为白细胞检测方式,采用VC6.0作为软件开发平台,建立了RBF神经网络的白细胞五分类识别算法模型,整个细胞识别和分类过程完全由软件实现,从而降低硬件复杂程度,减小了外界干扰因素的影响。实验结果：样机对LYM、MON、NEU、EOS、BAS的测试相对偏差分别为1.43%、4.41%、3.92%、2.94%、11.1%,满足了国家标准中的性能要求,故仪器整体的分类结果比较理想。结论：本文提出的智能光学系统具有性能稳定可靠、抗干扰能力强的特点。     

Synchronization of different chaotic systems via active radial basis functions sliding mode controller

This paper presents a new method to synchronize different chaotic systems with disturbances via an active radial basis function （RBF） sliding controller. This method incorporates the advantages of active control, neural network and sliding mode control. The main part of the controller is given based on the output of the RBF neural networks and the weights of these single layer networks are tuned on-line based on the sliding mode reaching law. Only several radial basis functions are required for this controller which takes the sliding mode variable as the only input. The proposed controller can make the synchronization error converge to zero quickly and can overcome external disturbances. Analysis of the stability for the controller is carried out based on the Lyapunov stability theorem. Finally, five examples are given to illustrate the robustness and effectiveness of the proposed synchronization control strategy.     

Locality properties of radial basis function expansion coefficients for equispaced interpolation

Natasha Flyer ^{Many types of radial basis functions (RBFs) are global in termsof having large magnitude across the entire domain. Yet, incontrast, e.g. with expansions in orthogonal polynomials, RBFexpansions exhibit a strong property of locality with regardto their coefficients. That is, changing a single data valuemainly affects the coefficients of the RBFs which are centredin the immediate vicinity of that data location. This localityfeature can be advantageous in the development of fast and well-conditionediterative RBF algorithms. With this motivation, we employ hereboth analytical and numerical techniques to derive the decayrates of the expansion coefficients for cardinal data, in both1D and 2D. Furthermore, we explore how these rates vary in theinteresting high-accuracy limit of increasingly flat RBFs.}     

Prediction of membrane spanning segments and topology in β‐barrel membrane proteins at better accuracy

Prediction of membrane spanning segments in β‐barrel outer membrane proteins (OMP) and their topology is an important problem in structural and functional genomics. In this work, we propose a method based on radial basis networks for predicting the number of β‐strands in OMPs and identifying their membrane spanning segments. Our method showed a leave‐one‐out cross validation accuracy of 96% in a set of 28 OMPs, which have the range of 8–22 β‐strand segments. The β‐strand segments in OMPs and the residues in membrane spanning segments are correctly predicted with the accuracy of 96% and 87%, respectively. We have developed a web server, TMBETAPRED‐RBF for predicting the transmembrane β‐strands from amino acid sequence and it is available at http://rbf.bioinfo.tw/～sachen/tmrbf.html . We suggest that our method could be an effective tool for predicting the membrane spanning regions and topology of β‐barrel membrane proteins. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

受扰统一混沌系统基于RBF网络的主动滑模控制

针对受外扰影响的统一混沌系统,提出一种基于径向基函数(RBF)神经网络的主动滑模自适应控制方法.将被控系统分解为受控子系统和自由子系统,利用主动控制思想,建立受控子系统在目标点处的状态误差的可控标准型,设计出一个结构简单的基于滑模趋近率在线参数整定的RBF函数神经网络控制器,并且基于Lyapunov稳定性理论分析了系统的稳定性.仿真结果表明该控制器对系统参数突变和外部干扰具有鲁棒性,同时抑制了抖振. 关键词： 统一混沌系统 主动控制 滑模控制 RBF网络     

克服扰动的混沌逆控制同步系统

基于自适应逆控制原理,在扰动存在的情况下,对混沌系统的同步问题进行了研究.研究表明本方法能有效地克服干扰对同步所造成的破坏,实现良好的同步效果.最后,利用Arneodo系统进行了仿真.仿真结果证明了所给方法的有效性 关键词： 混沌系统 同步 自适应逆控制 RBF神经网络     

稀土萃取分离过程软测量方法的研究

分析了稀土组分含量在线检测技术进展缓慢的原因,分析了稀土萃取分离过程机制,找出影响稀土组分含量检测的主要因素,确定辅助变量。利用从包钢稀土厂采集的数据通过newrb函数创建径向基网络来实现稀土组分含量的软测量。文中通过流程图详细阐述了建模方法,采用50组样本数据对所建立的模型进行计算机仿真验证,仿真结果证明了模型的可行性。     

Solution of time-domain acoustic wave propagation problems using a RBF interpolation model with “a priori” estimation of the free parameter

In the last decade, Meshless Methods have found widespread application in different fields of engineering and science. Beyond novelty, their mathematical simplicity and numerical accuracy have been the key of their rapid dissemination. Among meshless techniques, RBF (Radial Basis Functions) based methods can be simple and general to solve the problems related to multiple areas of applied physics and engineering. In the specific field of acoustics, there are usually two possible approaches for solving a problem: time- and frequency-domain. In this paper, the authors propose a local time-domain approach to establish an efficient methodology for the solution of large-scale acoustic wave propagation problems. For this purpose, a local interpolation scheme, based on the reproduction of the local wave field using RBFs (MultiQuadric and Gaussian), is implemented and its accuracy is verified against known closed-form solutions. An explicit time-domain marching procedure is adopted, and the quality of the numerical results is also compared with that obtained using standard space-time Finite-Difference schemes. Additionally, the RBF interpolation model is used to simulate the propagation of a Ricker pulse in two simple test cases, and applied to simulate a more complex configuration, corresponding to an underwater sound propagation problem. In this frame, the results are also compared with those computed using a fourth-order in space and second-order in time Finite-Difference scheme.