系统辨识

创发性DNA计算模型及其混沌系统辨识过程

Emergent DNA computational model and its chaotic system identification process

一种改进的BP网络系统辨识算法的研究

Study on a System Identification Algorithm of the Modified BP Network

基于Matlab系统辨识工具箱的系统建模

System Modeling Based on System Identification Toolbox in Matlab

一种鲁棒BP算法及其在非线性动态系统辨识中的应用

A robust BP algorithm and its application on the identification of nonlinear dynamic system

PID神经网络具有在线自学习能力，通过无教师的自学习方式，PID神经网络成功地实现了不同的系统辨识。

PID neural networks have the online self-studying ability and has successfully identified many different systems .

文章研究基于PID神经网络的多变量非线性动态系统辨识问题。

The paper is about the identify of multivariable nonlinear dynamic systems based on PID Neural Networks .

基于遗传BP算法的高斯基函数网络的非线性系统辨识

A novel identification method for nonlinear system based on Gaussian potential function networks with genetic back propagation algorithm

基于RBF神经网络的贴片机运动控制系统辨识

System Identification of Motion Control System on Placement Machine Based on RBF Network

非线性系统辨识的Taylor级数方法

Taylor series approach to non-linear systems identification

基于T-S模糊模型的神经网络的系统辨识

A System Identification for T-S Model Based on Neural Network

混沌机制在T-S模型模糊神经网络的系统辨识研究

Study on Chaotic Mechanism in System Identification Using T-S Model Fuzzy Neural Networks

本文在系统辨识原理的基础上，提出了一种在线确定水轮机蜗壳流量系数K的新方法，经计算机仿真试验检验，其精度不低于1.0%。

Based on the system identification theory , a new method to determine the discharge coefficient K of scroll case is presented in this paper .

基于Wiener模型的混沌系统辨识研究

Study of Chaos Identification Based on Wiener Model

Hopfield神经网络在SISO仿射非线性系统辨识与控制中的应用研究

Application of Hopfield Network in the Identification and Control of SISO Affine Nonlinear System

实现了线性系统辨识EM算法，提出了一种基于统计分析的算法初始化方法。

The EM algorithm for linear system identification is implemented and an initialization of the EM algorithm is proposed by using statistical analysis .

AR模型作为时间序列模型的一种，由于其参数估计和定阶简单而广泛用于系统辨识。

AR series , as one of time series models , is applied broadly in system identification because its parameter estimation and rank decision are simple .

基于GEP的非线性系统辨识算法

Non-linear System Recognition Algorithms Based on GEP

其次，采用改进的Elman动态递归神经网络进行工艺系统辨识；

Secondly , the algorithm of system identification based on improved Elman dynamic recursive neural network is used .

l1系统辨识中的代数算法及其Worst－case误差

The Algebra Algorithm and the Worst-case Error in l_1 System Identification

多维CARMA系统辨识的实践性研究

The practicable study of identification of multidimensional CARMA system

采用机理方法和系统辨识方法建立了苯酐生产过程带有纯滞后的二阶结构的数学模型，并设计出具有PID结构的自校正前馈控制器。

A two-order model for phthalic anhydride production process with time delay has been proposed with synthetic method of mechanism analysis and system identification , and a self-tuner with a feedforward PID structure has been designed .

本文基于系统辨识的最小二乘法，介绍一种用Basic语言编程的SISO线性系统系统辨识软件包及其原理、结构、功能与特点。

Based on the Least Squares Method , this paper introduces a sort of System Identification software package for SISO system in Basic Language as well as its principles , components , functions and characteristics .

DNN系统辨识及其在塑料挤出机中的应用

DNN-based system identification with applications to Plasticating extruders

针对非线性系统辨识问题，提出了一种基于Volterra级数模型的非线性系统的全解耦RLS自适应辨识算法。

Aiming at the identification problem for the nonlinear system , a fully decoupled RLS adaptive identification algorithm for nonlinear system based on Volterra series is presented in this paper .

人工神经网络（ANN）是一种用以模拟人类智能的复杂网络，现已广泛应用于智能控制、系统辨识、智能检测等领域。

Artificial Neural Network ( ANN ) is a complex network which could simulate some intelligent behaviors of human . It has been widely applied in the fields of intelligent control , system identification , and intelligent supervision etc.

该文介绍了最小模型误差估计算法（MME）和在非线性不确定系统辨识中的应用，以及分析了基于此算法的系统的鲁棒性的几个方面。

The Minimum Model Error ( MME ) and its application in nonlinear and uncertain systems are introduced in this paper .

非线性系统辨识一直是信号处理和控制理论的研究热点和难点。模糊RBF（Radialbasisfunction，RBF）神经网络结合了RBF神经网络和模糊推理的优点，具有强大的数据处理能力和非线性映射能力。

Nonlinear system identification is a focus and difficulty in signal processing and control theory * Fuzzy RBF ( Radial Basis Function ) neural network combines the advantages of the RBF neural network and fuzzy system with powerful data processing ability and nonlinear mapping ability .

针对已有的一个线性MIMO系统辨识方法没有充分利用累积量矩阵固有结构的不足，提出一个改进算法，从而提高估计性能。

Since an existing linear algorithm MIMO system doesn 't fully utilize inherent structure of cumulant matrix , we develop an improved algorithm to improve its performance of estimation .

接着通过系统辨识ARX模型对各层小波系数建模、获取模型残差序列，并探讨其在时间序列自适应预测方面的应用。

Then we modeling the wavelet coefficients of each level by ARX model . After modeling we obtain the outlier series and analyze its adaptive prediction in time series .

提出一种新的基于向量方法的自回归和运动平均（ARMA）模型系统辨识器，并给出了其参数的统计分析模型。

To present a new approach to auto-regressive and moving average ( ARMA ) modeling based on the support vector method , a statistical analysis of the characteristics of the proposed method is carried out .