代码搜索：optional
找到约 6,947 项符合「optional」的源代码
代码结果 6,947
www.eeworm.com/read/488590/6489872
cpp searchcmd.cpp
//----------------------------------------------------------------------
// Search
//----------------------------------------------------------------------
//
//
//
// search [-i] [-v] [-d] [-h]
www.eeworm.com/read/486493/6533372
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/485150/6566135
m checkparams.m
function s = checkparams(s, defaults, required)
%Verifies parameter structure and sets defaults for optional parameters
% [S] = CHECKPARAMS(S, DEFAULTS, REQUIRED)
% Verifies a parameter structure fo
www.eeworm.com/read/483033/6607886
m ukf_nmcda_predict_dp.m
%UKF_NMCDA_PREDICT_DP UKF/NMCDA Prediction step with target death processing
%
% Syntax:
% [S,EV_STRS] = ekf_nmcda_predict_dp(S,A,Q,a,AW,param,t,alpha,beta)
%
% In:
% S - Struct array 1xNP of pa
www.eeworm.com/read/483114/6609689
asv train.asv
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/483114/6609693
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/483114/6609761
asv train.asv
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/483114/6609767
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/478651/6712693
bas mdlquick.bas
Attribute VB_Name = "mdlQuick"
Option Explicit
Public Rst_DisPlayQuery As ADODB.Recordset
Public QuickTranCount As Integer, QuickTranArray() As String
Public Sub DisPlayQuery_SQL(ByVal vSql As S
www.eeworm.com/read/477304/6741468
m threshwave2.m
function out = ThreshWave2(Noisy,type,TI,sigma,mult,L,qmf)
% ThreshWave2 -- Denoising of 2-d image with wavelet thresholding.
% Usage
% out=ThreshWave2(Noisy,type,TI,sigma,mult,L,qmf)
% Inp