代码搜索：sequential
找到约 1,846 项符合「sequential」的源代码
代码结果 1,846
www.eeworm.com/read/193277/8242047
m bmilin.m
function diagnostic = bmilin(F,h,options)
%BMILIN Simple BMI solver based on sequential linearizations
%
% diagnostic = bmilin(F,h,options)
%
% EXTREMELY naive implementation of a local BMI solve
www.eeworm.com/read/200648/15428145
m contents.m
% Nonlinear multiresolution functions.
% Version 1.1 22-May-2006
%
% nmdemo - Nonlinear multiresolution demos.
%
% seqhaar - Sequential "S-transform" modified Haar wavelet.
www.eeworm.com/read/289680/8535103
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/188280/8552239
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/286105/8788358
m bookdemo.m
% PURPOSE : We address here a nonlinear non-Gaussian problem using
% the standard particle filtering algorithm.
% For more details refer to the introduction of our book:
% Sequential Monte Carlo in P
www.eeworm.com/read/428849/8834608
c smo_mex.c
/* --------------------------------------------------------------------
smo_mex.c: MEX-file for Sequential Minimal Optimizer.
Compile: mex smo_mex.c ../kernels/kernel_fun.c
Synopsis:
[Alpha,b
www.eeworm.com/read/183443/9158939
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/181389/9256531
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/181388/9256678
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/373595/9448984
c seq.c
/* Implementation of sequential features */
#include "defs.h"
#include "seq.h"
/* Parameter Handling */
#define DEFPOPSIZE 100
#define DEFMAXGEN 10000
#define DEFMAXERR 0.01
#define DEFSEED AUTO