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于 2021-03-03 发布文件大小:11KB

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Text attraction and my own code for good

文件列表：

matlab_code\text_extraction.m, 989 , 2017-12-13
matlab_code\text_extraction.asv, 989 , 2017-12-13
matlab_code\text_extraction_2.m, 443 , 2017-09-10
matlab_code\helperStrokeWidth.m, 2398 , 2017-09-10
matlab_code\text_extraction_example.m, 273 , 2017-09-10
matlab_code\confidence_index.mat, 128 , 2017-09-10
matlab_code\test_ext.m, 2493 , 2017-09-10
matlab_code\helperGrowEdges.m, 2204 , 2017-09-10
matlab_code\confidence_index.m, 881 , 2017-09-10
matlab_code\ocr1.m, 303 , 2017-09-10
matlab_code\helperDetectText.m, 8774 , 2017-09-10
matlab_code\text_extraction_3.m, 4579 , 2017-09-10

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说明：提出了一种改进高阶Butterworth低通滤波器性能的设计方法。首先对高阶Butterworth低通滤波器的极点进行重新分布，得出改进型Butterworth低通滤波器。性可以由其在基波电压初相位为零时的特性所唯一确定(Periodic voltage and current waveforms on the start time of its corresponding harmonic component of the relationship between the initial phase of research, pointed out that the characteristics of harmonic sources can be its initial phase in the fundamental zero-voltage characteristics of the CD a definite)

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积分：1
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lear N = 10^5 EB_NO = [-1:30] liu1 = zeros(1,N) liu2 = zeros(1,N) for ii = 1:length(EB_NO) m= (2*(rand(1,N)>0.5)-1) + j*(2*(rand(1,N)>0.5)-1) s = (1/sqrt(2))*m normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*randn(1,N)]

2012-05-17 19:56:01下载

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This program is prepared as an one-step EEG predictor. this is used a fuzzy neural network which is trained by a chaotic back propagation method

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2010-03-02 21:27:32下载

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2014-08-29 15:07:20下载

积分：1

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