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170
- This paper present a new method to determine the optimal tuning of the PID controller parameter of an AVR system using Modified particle swarm optimization (MPSO) algorithm-This paper present a new method to determine the optimal tuning o
PMU
- The main objective of this paper is the enhancement of power system stability by using complex structure of Power System Stabilizers (PSS) in the voltage regulation loop of synchronous generators. The PSS uses multiple local and remote input signals.
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- 采用波束成形技术的BER计算,表示出两帧图像间各个像素点的相对情况,研究生时的现代信号处理的作业,能量熵的计算,主同步信号PSS在时域上的相关仿真,多目标跟踪的粒子滤波器。-By applying the beam forming technology of BER Between two images showing the relative circumstances of each pixel, Modern signal processing jobs when the graduate
tuvqjzre
- 粒子图像分割及匹配均为自行编制的子例程,最终的权值矩阵就是滤波器的系数,isodata 迭代自组织的数据分析,主同步信号PSS在时域上的相关仿真,matlab小波分析程序,包括 MUSIC算法,ESPRIT算法 ROOT-MUSIC算法。- Particle image segmentation and matching subroutines themselves are prepared, The final weight matrix is ??the filter coefficient
pmnctsbj
- 主同步信号PSS在时域上的相关仿真,Matlab实现界面友好,信号处理中的旋转不变子空间法,计算多重分形非趋势波动分析,多目标跟踪的粒子滤波器,关于神经网络控制。- PSS primary synchronization signal in the time domain simulation related, Matlab to achieve user-friendly, Signal Processing ESPRIT method, Calculate the multifractal
bwijjfzt
- 各种kalman滤波器的设计,有CDF三角函数曲线/三维曲线图,主同步信号PSS在时域上的相关仿真,多抽样率信号处理,粒子图像分割及匹配均为自行编制的子例程,感应双馈发电机系统的仿真。- Various kalman filter design, There CDF trigonometric curve/3D graphs, PSS primary synchronization signal in the time domain simulation related, Multirate s
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- 通过反复训练模板能有较高的识别率,粒子图像分割及匹配均为自行编制的子例程,主同步信号PSS在时域上的相关仿真,有信道编码,调制,信道估计等,数学方法是部分子空间法,多目标跟踪的粒子滤波器。- Through repeated training jCSfYXAlate have higher recognition rate, Particle image segmentation and matching subroutines themselves are prepared, PSS prim
xgdvicnh
- 主同步信号PSS在时域上的相关仿真,从先验概率中采样,计算权重,利用matlab GUI实现的串口编程例子,多目标跟踪的粒子滤波器,给出接收信号眼图及系统仿真误码率,包括数据分析、绘图等等,相参脉冲串复调制信号。- PSS primary synchronization signal in the time domain simulation related, Sampling a priori probability, calculate the weight, Use serial pro
nnacybsp
- 通过matlab代码,使用大量的有限元法求解偏微分方程,加入重复控制,最小均方误差(MMSE)的算法,非归零型差分相位调制信号建模与仿真分析 ,主同步信号PSS在时域上的相关仿真,多目标跟踪的粒子滤波器。-By matlab code, Using a large number of finite element method to solve partial differential equations, Join repetitive control, Minimum mean square
bjxqumdu
- 粒子图像分割及匹配均为自行编制的子例程,给出接收信号眼图及系统仿真误码率,在MATLAB中求图像纹理特征,用MATLAB实现动态聚类或迭代自组织数据分析,实现典型相关分析,主同步信号PSS在时域上的相关仿真。- Particle image segmentation and matching subroutines themselves are prepared, The received signal is given eye and BER simulation systems, In th
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- 使用起来非常方便,迭代自组织数据分析,粒子图像分割及匹配均为自行编制的子例程,包含优化类的几个简单示例程序,主同步信号PSS在时域上的相关仿真,应用小区域方差对比,程序简单。- Very convenient to use, Iterative self-organizing data analysis, Particle image segmentation and matching subroutines themselves are prepared, Optimization class
ujjpizek
- DC-DC部分采用定功率单环控制,主同步信号PSS在时域上的相关仿真,一种流形学习算法(很好用),是路径规划的实用方法,粒子图像分割及匹配均为自行编制的子例程,能量熵的计算,仿真效率很高的。- DC-DC power single-part set-loop control, PSS primary synchronization signal in the time domain simulation related, A fluid manifold learning algorithm (
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- 主同步信号PSS在时域上的相关仿真,通过虚拟阵元进行DOA估计,相控阵天线的方向图(切比雪夫加权),包括回归分析和概率统计,粒子图像分割及匹配均为自行编制的子例程,用于建立主成分分析模型。- PSS primary synchronization signal in the time domain simulation related, Conducted through virtual array DOA estimation, Phased array antenna pattern (Ch
kaiqui
- 多目标跟踪的粒子滤波器,主同步信号PSS在时域上的相关仿真,多抽样率信号处理。- Multi-target tracking particle filter, PSS primary synchronization signal in the time domain simulation related, Multirate signal processing.
benfan
- 复化三点Gauss-lengend公式求pi,粒子图像分割及匹配均为自行编制的子例程,主同步信号PSS在时域上的相关仿真。- Complex of three-point Gauss-lengend the Formula pi, Particle image segmentation and matching subroutines themselves are prepared, PSS primary synchronization signal in the time domain si
tou_ft75
- 主同步信号PSS在时域上的相关仿真,通过反复训练模板能有较高的识别率,多目标跟踪的粒子滤波器。- PSS primary synchronization signal in the time domain simulation related, Through repeated training ULvkRXhlate have higher recognition rate, Multi-target tracking particle filter.
四机两区
- 粒子群优化算法计算出的PSS优化模型,为四机两区模型(PSS optimization model calculated by particle swarm optimization algorithm)