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dianji
异步电动机的矢量控制异步电动机是一个高阶、非线性、强耦合的多变量系统,使经典的交流电机理论和传统的控制系统分析方法不能完全适用于现代交流调速系统(Asynchronous motor vector controlled induction motor is a high-order, nonlinear, strongly coupled multivariable system, the classic theory of AC motor and control system analysis methods can not be fully applicable to the modern AC variable speed system)
- 2012-06-02 18:33:47下载
- 积分:1
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parraalgorithm
非稳定盲信号分离算法程序,可实现多个源信号分离。(Non-stable algorithm for blind signal separation procedures, separation of multiple source signals.)
- 2010-08-30 10:01:28下载
- 积分:1
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distance2d_point2line
Calculate point to line distance in 2D
- 2013-03-13 07:22:09下载
- 积分:1
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root_music
Root-MUSIC算法的matlab程序,这种算法为求根MUSIC算法,精确度高,缺点是当数值多时,运算速度慢(Root-MUSIC algorithm matlab program)
- 2021-03-24 12:49:14下载
- 积分:1
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LMS_eq
LMS Equalizer. implement equlizer with special channel rsponse
- 2014-02-24 02:31:14下载
- 积分:1
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NCMA
归一化恒模盲均衡算法的matlab仿真,并附有说明(Normalized constant modulus blind equalization algorithm matlab simulation, along with instructions)
- 2021-01-04 21:49:00下载
- 积分:1
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reval
Euclidean Distance Transform has been widely studied in computational geometry, image processing, computer graphics and pattern recognition. Euclidean distance has been computed through different algorithms like parallel, linear time algorithms etc. On the basis of efficiency, accuracy and numerical computations, existing and proposed techniques has been compared. This study proposed a new technique of finding Euclidian distance using sequential algorithm. An experimental evaluation has shown that proposed technique has reduced the drawbacks of existing techniques. And the use of sequential algorithm scans has reduced the computational cost.
- 2010-09-20 11:29:42下载
- 积分:1
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MY_MPSK
16 level PSK modulation and demodulation and the graph of Pb Vs SNR
- 2010-12-19 16:39:05下载
- 积分:1
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pp
说明: 基于MATLAB的PQ法潮流计算的计算机编程(flow)
- 2010-05-16 12:11:06下载
- 积分:1
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iris-classification-matlab-master
In this report, we devise a methodology for identifying the species of an iris amongst 3 based on 4 distinctive features. We first cover the constitution of the data set and input patterns. We then determine the layout and structure of the neural network we will use for the classification. We continue by testing the network in real life conditions. We conclude with a review of the methods used, and how they could be improved.
- 2014-09-21 00:53:28下载
- 积分:1