代码搜索：NI平台
找到约 10,000 项符合「NI平台」的源代码
代码结果 10,000
www.eeworm.com/read/177129/9468772
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/349842/10796670
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/464845/7060880
bas coloring.bas
Attribute VB_Name = "Coloring"
'This is the Module that Colorizes the contents of a
'richtextbox - defined by keywords
'I did not write or modify this so if you use this
'please give VBDiamond th
www.eeworm.com/read/463459/7180386
bat 对加密的代码进行解密处理.bat
@echo off
:: 对加密批处理进行解密处理
:: 原理：
:: for提取文本行不受编码格式制约,如果加密的代码是通过对文本文件头进行处理得来的话，
:: 可以用如下代码来还原。
if not exist ..\解密 md ..\解密
for %%i in (*.cmd) do (
del /a /f /q ..\解密\%%~ni.bat 2>nul
www.eeworm.com/read/316604/13520401
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/359185/6352492
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/493206/6398470
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/491099/6440567
m bernstein.m
function ni=bernstein(n,i) % Bernstein function n!/(i!*(n-i)!)
ni=factorial(n)/(factorial(i)*factorial(n-i));
www.eeworm.com/read/410924/11264786
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/151561/12200838
m m2.m
si=3:0.01:10;
mf=5;
ni=0.3;
y=3*mf^2*(mf+1);
z=si/ni;
plot(z,y*z)