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mm
说明: 化验结果诊断,程序详细,可以运行,欢迎下载(every )
- 2010-08-10 09:31:07下载
- 积分:1
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bpann
严格按照BP网络计算公式来设计的一个matlab程序,对BP网络进行了优化设计
优化1:设计了yyy,即在o(k)计算公式时,当网络进入平坦区时(<0.0001)学习率加大, 出来后学习率又还原
优化2:v(i,j)=v(i,j)+deltv(i,j)+a*dv(i,j) (A Matlab procedures in strict accordance with the BP network computing formula to design, the optimization design was carried out on BP network
Optimization design of 1: YYY, that is O (k) in the formula, when the network into the flat area (<0.0001) learning rate increase, after learning rate and reduction
Optimization of 2:v (I, J) =v (I, J)+deltv (I, J)+a*dv (I, J) )
- 2015-01-27 17:07:04下载
- 积分:1
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main
Threshold
Adaptive Threshold
- 2014-01-12 22:26:26下载
- 积分:1
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t MATLAB小波分析与应用 30个案例分析_14043787
小波分析的经典案例,很适合初学者学习。。。。。(Wavelet analysis of the classic case, very suitable for beginners to learn)
- 2021-04-08 09:59:00下载
- 积分:1
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打包
说明: 两种不同的假设:
H1 : 0 xn A fn wn ( ) cos(2 ) ( ) = ++ π θ n=1,2,…,N,f0 为规一化频率
H0 : xn wn () () = n=1,2,…,N
其中 w[n]是均值为 0,方差为 2 σ n 的高斯白噪声,A 已知,样本间相互
独立,信号与噪声相互独立; 相位θ 是随机变量,它服从均匀分布
1 0 2 ( ) 20 p
θ π θ π ?? ≤ ≤ = ??? 其它
1)改变输入信噪比(改变 A 或噪声方差均可),给定虚警概率,画出
输入信噪比与检测概率之间的理论曲线。(注意:理论检测曲线与样本
数有关) 2)改变样本数,用 Monte-Carlo 实验方法得出 PF=0.001 时输入信噪比
与检测概率之间关系曲线(至少三条),并得出结论。 3)改变 M-C 实验次数,样本数不变,用 Monte-Carlo 实验方法得出 PF =0.001 时输入信噪比与检测概率之间关系曲线(至少三条),并得出
结论。(Draw the theoretical curve between input SNR and detection probability)
- 2020-11-24 19:19:32下载
- 积分:1
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pro-4
this is matlab code for pprobality theory which is implemetatde in matab 7,6
- 2011-05-21 13:01:42下载
- 积分:1
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shaoshao
混合信号源发生器,可自己选择设置输入信号(Mixed Signal Generator can be set up to choose their own input signal)
- 2007-05-13 10:50:52下载
- 积分:1
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0490806DS_uwb_program
this is DS-UWB that I download from this is site
and I need every thing in UWB and CDMA fields
- 2013-03-10 18:44:06下载
- 积分:1
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godem
this code is simple and usful code it is a matlab code that optimize PID parametrs using Generic Algorithm
- 2011-12-06 22:02:48下载
- 积分:1
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ICAsuanfa
独立成分分析(Independent Component Analysis,ICA)是近年来提出的非常有效的数据分析工具,它主要用来从混合数据中提取出原始的独立信号。它作为信号分离的一种有效方法而受到广泛的关注。(Independent component analysis (Independent Component Analysis, ICA) is a very effective tool for data analysis proposed in recent years, it is mainly used to extract the original independent signals the mixed data. It is an effective method for signal separation and widespread concern.)
- 2015-03-27 00:55:41下载
- 积分:1