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于 2009-04-28 发布文件大小:4KB

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使用MATLAB编写的阴历和阳历转换程序(MATLAB prepared using the lunar calendar and Gregorian calendar conversion process)

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ti1
碎纸片的拼接，简单的几张一行图片进行链接。(Torn pieces of mosaic)

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FUZZY_ACDCSYSTEMS
This paper discusses the impact of HVDC on Power System Stability and proposes a new control mechanism based on Fuzzy set theory to augment dynamic performance of a multi-machine power system. To have good damping characteristics over a wide range of operating conditions, deviations in speed and acceleration of the machines are chosen as the input signals to the fuzzy controller. These input signals are first characterized by a set of linguistic variables using fuzzy set notations .The fuzzy relation matrix allows a set of fuzzy logic operations that are performed on controller inputs to obtain the desired output. The effectiveness of the proposed controller is demonstrated by a multi-machine system example. The performance of this fuzzy controller, in comparison to the conventional fixed gain controller, demonstrates the efficacy of this new fuzzy PID controller. Index Terms—HVDC, Eliminated variable

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04760221---
multi input pv for distributed applications

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本文介绍了使用MATLAB编写时间序列的方法，本文介绍了使用MATLAB编写时间序列的方法，(This article describes the preparation of time series using the MATLAB method of preparation of this article describes the use of MATLAB time series methods)

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lsm-rbf
说明：一种最小二乘法的RBF网络 ---------------------------------- radical basis function neural network ------------------------------------------ clear all close all global sp k w2 b2 unitcenters alldatanum=400 traindatanum=300 testdatanum=100 sp=8 errorlimit=0.1 u=rand(1,alldatanum+10) y=zeros(1,alldatanum+10) for i=4:alldatanum+3 y(1,i)=1.5*y(1,i-1)*y(1,i-2)*y(1,i-3)/(3+y(1,i-1)+y(1,i-2)*y(1,i-2)+... y(1,i-3)*y(1,i-3)*y(1,i-3))+u(1,i)+u(1,i-1)+u(1,i-2) 。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。(radical basis function neural network ------------------------------------------ clear all close all global sp k w2 b2 unitcenters alldatanum=400 traindatanum=300 testdatanum=100 sp=8 errorlimit=0.1 u=rand(1,alldatanum+10) y=zeros(1,alldatanum+10) for i=4:alldatanum+3 y(1,i)=1.5*y(1,i-1)*y(1,i-2)*y(1,i-3)/(3+y(1,i-1)+y(1,i-2)*y(1,i-2)+... y(1,i-3)*y(1,i-3)*y(1,i-3))+u(1,i)+u(1,i-1)+u(1,i-2) 。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。)

2011-04-13 10:26:06下载

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geometry2correlation
MIMO容量仿真的matlab程序，在相关影响情况下的容量分析(MIMO capacity matlab simulation procedures, the impact in the relevant circumstances of the Capacity Analysis)

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ofdm_HWJ
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