代码搜索：para
找到约 10,000 项符合「para」的源代码
代码结果 10,000
www.eeworm.com/read/266151/4274306
sgml glib-unused.sgml
The "GDesktopEntry" parser is intended to parse files written to
the
www.eeworm.com/read/266151/4274308
sgml base64.sgml
Base64 Encoding
encodes and decodes data in Base64 format
Base6
www.eeworm.com/read/415313/11076349
m perceptronkernel.m
% PerceptronKernel: implementation for kernel perceptron
%
% Parameters:
% para: parameters
% 1. Kernel: kernel type, 0: linear, 1: poly, 2: RBF, default: 0
% 2. KernelParam: kernel paramete
www.eeworm.com/read/415313/11076733
m gmm_classify.m
% GMM_classify: implementation for Gaussian mixture models
%
% Parameters:
% para: parameters
% 1. NumMix: number of Gaussian mixtures, default: 1
% 2. NCycles: number of iteration cycles, d
www.eeworm.com/read/415313/11076989
m mcactivelearning.m
% MCActiveLearning: implementation for active learning meta-classifier
%
% Parameters:
% para: parameters
% 1. Iter: iteration, default: 10
% 2. IncSize: data size per increment, default: 10
www.eeworm.com/read/248061/12603998
m ricestat.m
function [mu vr] = ricestat(v, s)
%RICESTAT Mean and variance of Rice/Rician probability distribution.
% [mu vr] = ricepdf(v, s) returns the mean and variance of the Rice
% distribution with para
www.eeworm.com/read/235546/14064139
asv ofdm_fading.asv
% ofdm_fading.m
%
%
% programmed by T.Yamamura and H.Harada
%
function[ber,per]=ofdm_fading(snr_in_db)
%********************** preparation part ***************************
para=64; % Numb
www.eeworm.com/read/132622/14082737
asm creat.asm
public begin
desg segment para 'data'
filename label byte
maxname db 16
namelen db ?
pathnam db 16 dup (' ')
long equ 1024
file db long d
www.eeworm.com/read/109732/15551253
asm creat.asm
public begin
desg segment para 'data'
filename label byte
maxname db 16
namelen db ?
pathnam db 16 dup (' ')
long equ 1024
file db long d
www.eeworm.com/read/175615/9539876
m nettrain.m
%此为BP网络训练程序,采用BP神经网络算法中的LM算法实现
%样本数据来源于数据.xls,数据保存在input_para1.txt文件中，output_para1.txt文件对应分类结果，示例
%中为5类
function retstr = NetTrain(ModelNo,NetPara,TrainPara,InputFun,OutputFun,DataDir)
NNTWARN OFF