搜索资源列表
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2下载：
线性系统中的子空间辨识算法，英文书配套的MATLAB程序-linear system of subspace identification algorithm, English books supporting MATLAB program
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A Matlab toolbox for exact linear time-invariant system identification is presented. The emphasis is on the variety of possible ways to implement the mappings from data to parameters of the data generating system. The considered system representatio
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《MATLAB控制系统仿真与实例详解》一书的光盘源码。图书简介：本书详细地讲解了MATLAB 7.x的功能与相关操作以及MATLAB在控制系统中的仿真应用。本书内容包括控制系统仿真基础、MATLAB程序设计语言基础、控制系统理论基础、Simulink交互式仿真环境、控制系统建模、线性控制系统的分析与仿真、PID控制系统设计及仿真、最优控制系统设计、鲁棒控制系统设计、神经网络系统设计及其MATLAB实现、模糊控制系统设计和系统辨识。
-" MATLAB Control System S
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利用神经网络对输入的Ｍ序列进行线性离散系统辨识，及其改进算法-The use of neural network input M-sequence of linear discrete-time system identification, and its improved algorithm
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This addresses the use of ANFIS function in the Fuzzy Logic Toolbox for nonlinear dynamical system identification. This
also requires the System Identification Toolbox, as a comparison is made between a nonlinear ANFIS and a linear ARX model.
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在matlab中利用Volterra非线形滤波器进行系统辨识，并带有一个应用示例。代码带有详细注释。-In the matlab filter using Volterra non-linear system identification, and with an application example. Code with detailed comments.
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CUED系统识别工具箱，包括：
1 Subspace identification of linear systems.
2 Subspace identification of bilinear systems-CUED System Identification Toolbox:
1 Subspace identification of linear systems.
2 Subspace identification of bilinear systems
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一次完成最小二乘算法小程序，在单输入单输出线性系统辨识中的应用。-Least squares algorithm applet one time, in the single-input single-output linear system identification applications.
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精密控制结构需要满足先进飞机的使命和对其引航的要求。这就要求飞行器的性能必须满足在低空飞行，低速飞行和大迎角攻击性飞行，全天候，昼夜工作的条件，并且新的控制技术应该成熟。这项工作提出了飞行控制时，状态变量和控制输入是由预先确定的限制范围内的系统控制系统的设计理念。在设计过程使用动态规划的概念。其基本思想涉及非二次泛函最小化。由于一系列限制因素，建议使用光滑函数。同时提出了该综合方法的优点。我们利用对F-18战斗机的纵向控制配置来说明该设计方法。-Indirect adaptive control
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第七章的多维非线性辨识的MATLAB程序例7.2用神经网络学习二维非线性函数
，是侯媛彬和汪梅的系统辨识课本上第七章的的实验。-Chapter VII of the multi-dimensional non-linear identification procedure Example 7.2 using the MATLAB neural network to learn two-dimensional nonlinear function, is Houyuan Bin and Wan
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本实验隶属现代数字信号处理，涉及到谱估计和谱分解，对学习数字信号的现代处理方法帮组很大。系统辨识实验实现：输入为功率为1（方差为1）的白噪声信号，通过一个线性移不变（LSI）系统，采用功率谱分析方法实现系统辨识对一个LSI系统进行辨识,并比较最后辨识出的系统与原系统的差别，分别显示出来。
-Experimental realization of system identification: input power of 1 (variance 1) of the white noise si
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Title: "Voice Recognition and Identification system".
Mainly involves:
1: Human speaker recognition
2: Technical data of samples
3: linear and logarithmic power spectrum plot
4: Plots for different values for N
5: Mel Space
6:
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关于非线性离散系统辨识，光纤无线通信系统中传输性能的研究，进行逐步线性回归。- Nonlinear discrete system identification, Fiber Transmission wireless communication system performance, Stepwise linear regression.
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直线阵采用切比学夫加权控制主旁瓣比，LZ复杂度反映的是一个时间序列中，关于非线性离散系统辨识。- Linear array using cut than learning laid upon the right control of the main sidelobe ratio, LZ complexity is reflected in a time sequence, Nonlinear discrete system identification.
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关于非线性离散系统辨识，进行逐步线性回归，使用混沌与分形分析的例程。- Nonlinear discrete system identification, Stepwise linear regression, Use Chaos and fractal analysis routines.
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雅克比迭代求解线性方程组课设,关于非线性离散系统辨识，isodata 迭代自组织的数据分析。- Jacobi iteration for solving linear equations class-based, Nonlinear discrete system identification, Isodata iterative self-organizing data analysis.
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数学方法是部分子空间法，雅克比迭代求解线性方程组课设,关于非线性离散系统辨识。- Mathematics is part of the subspace, Jacobi iteration for solving linear equations class-based, Nonlinear discrete system identification.
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雅克比迭代求解线性方程组课设,关于非线性离散系统辨识，实现了图像的加水印，去噪，加噪声等功能。- Jacobi iteration for solving linear equations class-based, Nonlinear discrete system identification, Realize image watermarking, de-noising, plus noise and other functions.
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程序功能分别实现了线性系统理论中传递函数和状态空间的相互转化，系统辨识中的递推最小二乘算法，免疫算法以及神经网络中的BP算法。-The program functions respectively realize the mutual transformation of transfer function and state space in the linear system theory, the recursive least squares algorithm in the system
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This paper describes the application of an identification algorithm clustering type Gustafson-Kessel nonlinear
dynamical system. From input-output data the algorithm generates fuzzy models of Takagi-Sugeno. This type of modeling is applied
to a non
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