代码搜索：Learning
找到约 5,352 项符合「Learning」的源代码
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www.eeworm.com/read/389692/8507163
m genparam.m
function mf_param = genparam(data,mf_n,mf_type)
%GENPARAM Generate initial membership function parameters for ANFIS learning.
% GENPARAM(DATA,MF_N,MF_TYPE) generates initial input MF parameters
%
www.eeworm.com/read/377948/9256244
m nnd14cl.m
function nnd14cl(cmd,arg1,arg2,arg3)
%NND14CL Competitive learning demonstration.
%
% This demonstration requires either the MININNET functions
% on the NND disk or the Neural Network Toolbox.
www.eeworm.com/read/180274/9313854
cpp aggregating.cpp
/** @file
* $Id: aggregating.cpp 2511 2005-11-23 03:34:52Z ling $
*/
#include
#include "aggregating.h"
namespace lemga {
/** Delete learning models stored in @a lm. This is only used
www.eeworm.com/read/371501/9551123
m ffperceptron.m
%QUESTION NO:2
%Using the Perceptron Learning Law design a classifier for the following
%problem:
% Class C1 : [-2 2]', [-2 1.5]', [-2 0]', [1 0]' and [3 0]'
% Class C2 : [ 1 3]', [3 3]', [1 2]'
www.eeworm.com/read/361257/10062628
m nnd14cl.m
function nnd14cl(cmd,arg1,arg2,arg3)
%NND14CL Competitive learning demonstration.
%
% This demonstration requires either the MININNET functions
% on the NND disk or the Neural Network Toolbox.
www.eeworm.com/read/359005/10171538
m genparam.m
function mf_param = genparam(data,mf_n,mf_type)
%GENPARAM Generate initial membership function parameters for ANFIS learning.
% GENPARAM(DATA,MF_N,MF_TYPE) generates initial input MF parameters
%
www.eeworm.com/read/424119/10490910
c h2m_glvq_model.c
/*
Harmonic to Minimum Generalized Learning Vector Quantization (H2M-GLVQ) classification algorithm.
Usage
------
[Wproto_est , yproto_est , E_H2MGLVQ] = h2m_glvq_model(Xtrain , yt
www.eeworm.com/read/351010/10688169
m nnd14cl.m
function nnd14cl(cmd,arg1,arg2,arg3)
%NND14CL Competitive learning demonstration.
%
% This demonstration requires either the MININNET functions
% on the NND disk or the Neural Network Toolbox.