代码搜索：optional
找到约 6,947 项符合「optional」的源代码
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www.eeworm.com/read/264784/11301749
bas basregistry.bas
Attribute VB_Name = "basRegistry"
Option Explicit
Const DCP_AUTHN_LEVEL_DEFAULT = 0
Const DCP_AUTHN_LEVEL_NONE = 1
Const DCP_AUTHN_LEVEL_CONNECT = 2
Const DCP_AUTHN_LEVEL_CALL = 3
Const DCP_AU
www.eeworm.com/read/264167/11326965
h connection.h
// OraLib 0.0.3 / 2002-06-30
// connection.h
//
// http://606u.dir.bg/
// 606u@dir.bg
#ifndef _CONNECTION_H
#define _CONNECTION_H
namespace oralib {
class statement;
class resultset
www.eeworm.com/read/264167/11326972
h error.h
// OraLib 0.0.3 / 2002-06-30
// error.h
//
// http://606u.dir.bg/
// 606u@dir.bg
#ifndef _ERROR_H
#define _ERROR_H
namespace oralib {
// error codes thrown from the library
enum Err
www.eeworm.com/read/409393/11328534
bas mdlnotify.bas
Attribute VB_Name = "mdlNotify"
'****************************************************************************
'人人为我，我为人人
'枕善居收藏整理
'发布日期：2007/03/15
'描 述：网页搜索音乐播放器 Ver 1.1.0
'网 站：http://www
www.eeworm.com/read/407295/11422493
m erts_smooth1.m
%ERTS_SMOOTH1 Extended Rauch-Tung-Striebel smoother
%
% Syntax:
% [M,P,D] = ERTS_SMOOTH1(M,P,A,Q,[a,W,param,same_p])
%
% In:
% M - NxK matrix of K mean estimates from Unscented Kalman filter
%
www.eeworm.com/read/407295/11422543
bak kf_predict.m.bak
%KF_PREDICT Perform Kalman Filter prediction step
%
% Syntax:
% [X,P] = KF_PREDICT(X,P,A,Q,B,U)
%
% In:
% X - Nx1 mean state estimate of previous step
% P - NxN state covariance of previ
www.eeworm.com/read/407295/11422544
m kf_predict.m
%KF_PREDICT Perform Kalman Filter prediction step
%
% Syntax:
% [X,P] = KF_PREDICT(X,P,A,Q,B,U)
%
% In:
% X - Nx1 mean state estimate of previous step
% P - NxN state covariance of previ
www.eeworm.com/read/407295/11422545
m lti_disc.m
%LTI_DISC Discretize LTI ODE with Gaussian Noise
%
% Syntax:
% [A,Q] = lti_disc(F,L,Qc,dt)
%
% In:
% F - NxN Feedback matrix
% L - NxL Noise effect matrix (optional, default ide
www.eeworm.com/read/402890/11526620
m susan.m
%function [U,V,USAN] = SUSAN(A,maxInt,sigma,thresh,g,radius,width)
%
% Returns the USAN response of a greysale image
%
% INPUT:
% A - the image. Intensity must be quantized as integers with a mi
www.eeworm.com/read/400577/11573353
m svc_nu.m
%SVC_NU Support Vector Classifier: NU algorithm
%
% This routine is outdated, use NUSVC instead
%
% [W,J,C] = SVC(A,TYPE,PAR,NU,MC,PD)
%
% INPUT
% A Dataset
% TYPE Type of the kernel (opti