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/333209/7154836
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/460435/7251169
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% This routine is outdated, use NUSVC instead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
www.eeworm.com/read/459928/7262286
c ndlms_t.c
//*****************************************************************************
// Filename: ndlms_t.c
// Version: 0.01
// Description: test for ndlms routine
//******************************
www.eeworm.com/read/459928/7262514
bak nblms_t.c.bak
//*****************************************************************************
// Filename: nblms_t.c
// Version: 0.01
// Description: test for nblms routine
//******************************
www.eeworm.com/read/459928/7262521
c nblms_t.c
//******************************************************************************
// Filename: nblms_t.c
// Version: 0.01
// Description: test for nblms routine
//*****************************
www.eeworm.com/read/459593/7273115
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)
% Input
www.eeworm.com/read/458493/7295534
m demoargs.m
function [out1,out2] = demoArgs(in1,in2,in3)
% demoArgs Variable numbers of input and output parameters
%
% Synopsis: demoArgs
% demoArgs(in1)
% demoArgs(in1,in2)
%
www.eeworm.com/read/458493/7295632
m drawplane.m
function drawPlane(a,bounds,axlim,addAxes)
% drawPlane Draws a plane in 3D
%
% Synopsis: drawPlane(a)
% drawPlane(a,bounds)
% drawPlane(a,bounds,axlim)
% drawP
www.eeworm.com/read/458493/7295674
m powerit.m
function [lambda,v] = powerit(A,s,nit,x0,verbose)
% powerit Shifted power method for finding matrix eigenvalues
%
% Synopsis: lam = powerit(A) [lam,v] = powerit(A)
%