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Wear-Leveling
Wear Leveling Algorithm 內部功能介紹(Wear Leveling Algorithm)
- 2014-10-30 14:43:04下载
- 积分:1
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multiwavelet
多小波变换MATLAB源程序,m文件形式给出,经调试能正确运行。(multiwavelet transform.)
- 2009-04-03 19:09:33下载
- 积分:1
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ImageCompressionUsingDCT
The discrete cosine transform (DCT) is a technique for converting a signal into elementary
frequency components. It is widely used in image compression. Here we develop some simple
functions to compute the DCT and to compress images.
These functions illustrate the power of Mathematica in the prototyping of image processing
algorithms.
The
- 2009-12-11 15:13:34下载
- 积分:1
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palaniselvi2
matlab program for power system
- 2011-08-21 18:20:19下载
- 积分:1
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Wavelet-Transform-C-
小波变换C语言实现,包含小波变换中各种算法,可以进一步了解算法的具体过程(Wavelet Transform C Language Realization)
- 2021-04-19 09:18:51下载
- 积分:1
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kuopinxunhuanpu
计算扩展频带信号的循环谱 对循环相关感兴趣者下载(Calculation of the expansion of the cyclic spectrum band signals related to the cycle of interest to those who download)
- 2009-01-03 15:24:40下载
- 积分:1
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zidongkongzhiyuanli
自动控制原理的实验报告,实验通过matlab软件完成,在matlab下变成通过,报告中附带图片,所有代码以图片给出(Automatic Control Theory lab reports, experiments done by matlab software, to become, in matlab by the report included pictures, all pictures are given the code to)
- 2010-12-30 10:50:05下载
- 积分:1
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MadaProgramme
Code Source DFIG Model
- 2014-08-28 15:46:04下载
- 积分:1
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cc_grids_constrained
CC_GRIDS_CONSTRAINED computes CC orders and grids satisfying a constraint.
- 2012-09-01 16:40:18下载
- 积分:1
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elm_example
极限学习机(extreme learning machine)ELM是一种简单易用、有效的单隐层前馈神经网络SLFNs学习算法。2006年由南洋理工大学黄广斌副教授提出。传统的神经网络学习算法(如BP算法)需要人为设置大量的网络训练参数,并且很容易产生局部最优解。极限学习机只需要设置网络的隐层节点个数,在算法执行过程中不需要调整网络的输入权值以及隐元的偏置,并且产生唯一的最优解,因此具有学习速度快且泛化性能好的优点。(Extreme Learning Machine (extreme learning machine) ELM is an easy-to-use and effective single hidden layer feedforward neural network the SLFNs learning algorithm. 2006 by the Nanyang Technological University Associate Professor Huang Guangbin. Traditional neural network learning algorithm (BP) artificial network training parameters, and it is easy to generate a local optimal solution. Extreme Learning Machine network only need to set the number of hidden nodes, the algorithm implementation process does not need to adjust the network input weights and hidden element of bias, and only optimal solution, so the learning speed and generalization good performance advantages.)
- 2013-03-29 13:05:47下载
- 积分:1