代码搜索：Generalized
找到约 2,645 项符合「Generalized」的源代码
代码结果 2,645
www.eeworm.com/read/255595/12069827
m ex5_1.m
% Example 5-1: Computation of Time-varying Channel
% Transfer Matrix Wc
clear all
K = 4; % Number of time samples (I/O observations)
N = 4; % Number of channel inputs
M = 4; % Number of channel
www.eeworm.com/read/253950/12173595
m glminit.m
function net = glminit(net, prior)
%GLMINIT Initialise the weights in a generalized linear model.
%
% Description
%
% NET = GLMINIT(NET, PRIOR) takes a generalized linear model NET and
% sets the weig
www.eeworm.com/read/253950/12174196
htm glminit.htm
Netlab Reference Manual glminit
glminit
Purpose
Initialise the weights in a generalized linear model.
Synopsis
www.eeworm.com/read/253950/12174236
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/339665/12211592
m glminit.m
function net = glminit(net, prior)
%GLMINIT Initialise the weights in a generalized linear model.
%
% Description
%
% NET = GLMINIT(NET, PRIOR) takes a generalized linear model NET and
% sets the weig
www.eeworm.com/read/339665/12211944
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/150905/12250398
htm glminit.htm
Netlab Reference Manual glminit
glminit
Purpose
Initialise the weights in a generalized linear model.
Synopsis
www.eeworm.com/read/150905/12250470
m glminit.m
function net = glminit(net, prior)
%GLMINIT Initialise the weights in a generalized linear model.
%
% Description
%
% NET = GLMINIT(NET, PRIOR) takes a generalized linear model NET and
% sets the weig
www.eeworm.com/read/150905/12250686
m demglm2.m
%DEMGLM2 Demonstrate simple classification using a generalized linear model.
%
% Description
% The problem consists of a two dimensional input matrix DATA and a
% vector of classifications T. The da
www.eeworm.com/read/150760/12265727
m pandr.m
function varargout = pandr(model,distrib)
% PANDR Visualizes solution of the Generalized Anderson's task.
%
% Synopsis:
% h = pandr(model)
%
% Description:
% It vizualizes solution of the Gen