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电力系统静态稳定计算一般采用小干扰法，即首先计算近似的线性微分方程组系数矩阵的特征根。然后根据特征根在复平面上的特性，判别电力系统运行的稳定性
操作说明：
请输入初始功率S0，形如a+bi
请输入无限大系统母线电压V0
请输入系统直轴等值电抗的大小Xd
请输入同步电角速度
请输入惯性时间常数Tj
请输入综合阻尼系数D-static power system stability calculation generally use small interfering, f
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这个程序可以识别图像中的线段或者直线，算法采用哈夫变换，将直线变换为另一个坐标系中的点，进而完成识别。-this procedure can identify the image or straight line segments, Hough transform algorithm. Linear transformation of coordinate system to another's point, thus completing the identification.
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The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is
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************************************************************************ * * * * * THIS IS THE H Y P L A S 2.0 README FILE * * ----------------- * * * * HYPLAS is a finite element program for implicit small and large * * strain analisys of hyperelast
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它是SourceForge上的一个开源项目，使用Malib实现实时处理，CSU Face Identification Evaluation System进行人脸识别。算法包括：主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)等等
Malic is realtime face recognition system
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高斯网络的非线性动态系统直接逆模型辨识，为一并联结构-The Gauss network non-linear dynamic system direct counter model identification, is a parallel structure
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Rapid Controller Prototyping (RCP) requires two components:
a Computer Aided Control System Design (CACSD)
software and a dedicated hardware with a hard real-time
operating system. The software should allow to perform all
phases of control sy
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Descr iption
We present a Matlab toolbox which can solve basic problems related to the Total Least Squares (TLS) method in the modeling. By illustrative examples we show how to use the TLS method for solution of:
- linear regression model
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基于SVR的线性系统逆模型辨识建模及校验的仿真程序，由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同。-Linear inverse model identification modeling and verification system simulation program based on SVR identification signal are random signal, not the value of the fixed signal, s
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基于SVR的线性系统内部模型辨识建模及校验的仿真程序， 由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同。-Based the SVR system of linear internal model identification modeling and verification simulation program identification signal are random signal, not the value of the fixed si
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在程序设计和调试过程中①只要在程序中增加类似m或n的循环语句，便可用神经网对三维或三维以上的非线形函数训练，也可以用在复杂系统二个以上独立变量、任意维非线性动态参数的辨识-In program design and debugging process ① similar increase in the program as long as m or n of the loop, you can use the neural network over a three-dimensional or
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雅克比迭代求解线性方程组课设,计算时间和二维直方图,关于非线性离散系统辨识。- Jacobi iteration for solving linear equations class-based, Computing time and two-dimensional histogram, 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，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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该程序是基于《时滞系统的辨识及NARMAX模型的修正》论文编写的matlab程序-The program is based on the identification and correction of NARMAX model of a class of linear system papers written in matlab
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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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BP神经网络的整个训练过程,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。- The entire training process BP neural network, 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，供做算法研究人员参考。- Jacobi iteration for solving linear equations class-based, Nonlinear discrete system identification, Algorithm for researchers to do reference.
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Linear array using cut than learning laid upon the right control of the main sidelobe ratio, HARQ throughput analysis of the system, Nonlinear discrete system identification.
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