代码搜索：Variance

找到约 2,271 项符合「Variance」的源代码

代码结果 2,271
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/237137/4631652

m new_turbo_ic.m

function [x_intf,x_sigma]= New_Turbo_IC(x_rake,Former_Rou,Former_Mask,Latter_Rou,Latter_Mask, Noise_variance,x_mean,x_variance,SubslotData_length,Path_number,Det_intl_table,nIter) % Gray coded 16
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www.eeworm.com/read/291752/8397892

dat danpdgm.dat

$ system Date_In_Short_Rpt_Name = false Date_In_Full_Rpt_Name = false Max_Pass_Number = 2000 $ sig_anchr samp_intvl = 0.125 block_size = 1024 $ ar_sig_source Noise_Seed = 113559 Driving_Va
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www.eeworm.com/read/291752/8397961

dat sampspect.dat

$ system Date_In_Short_Rpt_Name = false Date_In_Full_Rpt_Name = false Max_Pass_Number = 2000 $ sig_anchr xamp_intvl = 0.0078125 samp_intvl = 0.125 block_size = 1024 $ ar_sig_source Noise_S
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www.eeworm.com/read/291752/8398001

dat bartpdgm.dat

$ system Date_In_Short_Rpt_Name = false Date_In_Full_Rpt_Name = false Max_Pass_Number = 4000 $ sig_anchr xamp_intvl = 0.0078125 samp_intvl = 0.125 block_size = 1024 $ ar_sig_source Noise_S
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www.eeworm.com/read/189641/8464233

m resample_particles.m

function particles= resample_particles(particles, Nmin, doresample) %function particles= resample_particles(particles, Nmin, doresample) % % Resample particles if their weight variance is such that
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www.eeworm.com/read/386050/8767595

m gendatb.m

%GENDATB Generation of banana shaped classes % % A = GENDATB(N,S) % % INPUT % N number of generated samples of vector with % number of samples per class % S variance
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www.eeworm.com/read/386050/8768320

m subsc.m

%SUBSC Subspace Classifier % % W = SUBSC(A,N) % W = SUBSC(A,FRAC) % % INPUT % A Dataset % N or FRAC Desired model dimensionality or fraction of retained % variance per
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www.eeworm.com/read/299984/7140048

m gendatb.m

%GENDATB Generation of banana shaped classes % % A = GENDATB(N,S) % % INPUT % N number of generated samples of vector with % number of samples per class % S variance
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www.eeworm.com/read/299984/7140361

m subsc.m

%SUBSC Subspace Classifier % % W = SUBSC(A,N) % W = SUBSC(A,FRAC) % % INPUT % A Dataset % N or FRAC Desired model dimensionality or fraction of retained % variance per
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www.eeworm.com/read/460435/7250523

m gendatb.m

%GENDATB Generation of banana shaped classes % % A = GENDATB(N,S) % % INPUT % N number of generated samples of vector with % number of samples per class % S variance
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