代码搜索：parameter
找到约 10,000 项符合「parameter」的源代码
代码结果 10,000
www.eeworm.com/read/251685/12325915
m chap3_3.m
%Fuzzy Immune PID Control
clear all;
close all;
a=newfis('fuzz_ljk');
f1=1.0;
a=addvar(a,'input','u',[-f1*1,f1*1]); %Parameter e
a=addmf(a,'input',1,'NB','zmf',[-f1*1,f1*1]);
a=
www.eeworm.com/read/251685/12325921
m chap3_2.m
%Fuzzy Tunning PID Control
clear all;
close all;
a=newfis('fuzzpid');
a=addvar(a,'input','e',[-3,3]); %Parameter e
a=addmf(a,'input',1,'NB','zmf',[-3,-1]);
a=addmf(a,'
www.eeworm.com/read/251566/12337095
cpp hicdoc.cpp
// HICDoc.cpp : implementation of the CHICDoc class
//
#include "stdafx.h"
#include "HIC.h"
#include "ARITHCoding.h"
#include "HICDoc.h"
#include "SPIHTCoder.h"
#include "math.h"
#include "D
www.eeworm.com/read/251528/12339439
m ut_mweights.m
%UT_MWEIGHTS - Generate matrix form unscented transformation weights
%
% Syntax:
% [WM,W,c] = ut_mweights(n,alpha,beta,kappa)
%
% In:
% n - Dimensionality of random variable
% alpha - Transf
www.eeworm.com/read/251528/12339456
m utf_smooth1.m
%UTF_SMOOTH1 Smoother based on two unscented Kalman filters
%
% Syntax:
% [M,P] = UTF_SMOOTH1(M,P,Y,[ia,Q,aparam,h,R,hparam,,alpha,beta,kappa,mat,same_p_a,same_p_h])
%
% In:
% M - NxK matrix of K
www.eeworm.com/read/337735/12343725
v nco_dds_st.v
// Copyright (C) 1988-2006 Altera Corporation
// Any megafunction design, and related net list (encrypted or decrypted),
// support information, device programming or simulation file, and any other
/
www.eeworm.com/read/337735/12347111
v nco_sin_st.v
// Copyright (C) 1988-2006 Altera Corporation
// Any megafunction design, and related net list (encrypted or decrypted),
// support information, device programming or simulation file, and any other
/
www.eeworm.com/read/149739/12353465
m parzenml.m
%PARZENML Optimum smoothing parameter in Parzen density estimation.
%
% H = PARZENML(A,FID)
%
% INPUT
% A input dataset
% FID File ID to write progress to (default [], see PRPROGRESS)
%
%
www.eeworm.com/read/149739/12353979
m sigm.m
%SIGM Sigmoid map
%
% W = W*SIGM
% B = A*SIGM
% W = W*SIGM([],SCALE)
% B = SIGM(A,SCALE)
%
% INPUT
% A Dataset (optional)
% SCALE Scaling parameter (optional, default: 1)
%
%
www.eeworm.com/read/251250/12355690
m pcafea.m
%this function is used to obtain PCA feature of a single image
%feature: obtained pca feature of the immat as return value (m*1 vector)
%immat: the image wati to be processed (n*1 vector)
%av