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PSO
基于粒子群的神经网络优化算法的应用,在土壤水分特征曲线中的应用。(Neural network based on particle swarm optimization algorithm applied in the soil moisture characteristic curve application.)
- 2013-10-18 13:44:10下载
- 积分:1
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waveletMLR_longchuan
可以用于预测的小波分解下的多元线性回归,对于径流预测有效(wavelet mlr)
- 2015-03-31 16:43:19下载
- 积分:1
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iris_code_final
it is a program to identify the persons using his own iris
- 2010-07-23 02:06:42下载
- 积分:1
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MCKD
所传代码主要功能是通过MCKD算法对故障信号进行故障特征频率的提取(The main function of the code is to extract the fault characteristic frequency of the fault signal by MCKD algorithm)
- 2020-11-05 16:39:50下载
- 积分:1
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rx_find_packet_edge
说明: OFDM的FIND PACKET仿真,是用Matlab编程实现的(OFDM FIND PACKET simulation, using the Matlab programming)
- 2005-11-30 13:27:33下载
- 积分:1
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digital-communication
说明: 数字通信16QAM,16QPSK的实现思路及分析,报告详细,有误码率的分析(Digital communication 16QAM, 16QPSK implementation ideas and analysis, report details, there is the analysis of bit error rate)
- 2011-03-17 12:32:05下载
- 积分:1
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RTD
this is random decermin technique for mode estimation with wavelet techiniq
- 2012-10-24 18:44:33下载
- 积分:1
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5
说明: 用Newton插值多项式和三次样条插值多项式,已知f(x)=1/(1+25x^2)(With the Newton interpolation polynomial and cubic spline interpolation polynomial, known f (x) = 1/(1+25 x ^ 2))
- 2010-08-26 21:13:35下载
- 积分:1
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simulate1
直接序列扩频(DS)原理的仿真程序,通过该程序你可以很好地理解直接序列扩频原理。(Direct Sequence Spread Spectrum (DS) The principle of simulation program, through the program you can very well understand the principle of direct sequence spread spectrum.)
- 2008-03-27 21:19:31下载
- 积分:1
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work
matlab 关于association rule 的自己写的函数,有3个文件,
association.m:h = association(m, i, j)
i=>j, m是数据,h是support和confidence,该函数只适用于单个数据
ass_item: h=ass_itset(m, a, b)
同上,但是可用于多个数据(m为数组)
assrule: h = assrule(m, threshold1, threshold2)
该函数用于classification, 得到规则,threshold1为要求的support,threshold2为要求的confidence,h 则为符合要求的规则及其support和confidence,前2列为规则,后2列为其support和confidence
(matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data
ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix)
assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)
- 2009-12-15 02:51:44下载
- 积分:1