代码搜索：Non-linear
找到约 518 项符合「Non-linear」的源代码
代码结果 518
www.eeworm.com/read/477110/6747960
m check1.m
%CHECK script to compare M-file and MEX-file versions of RNE
% load the model and remove non-linear friction
rdh = nofriction(rdh, 'coulomb');
rmdh = nofriction(rdh, 'coulomb');
% number of trials
n
www.eeworm.com/read/255755/12057999
m nlfisherm.m
%NLFISHERM Non-linear Fisher Mapping according to Marco Loog
%
% W = NLFISHERM(A,N)
%
% INPUT
% A Dataset
% N Number of dimensions (optional; default: MIN(K,C)-1, where
% K is the di
www.eeworm.com/read/152430/12115056
m truth.m
function T = truth(seed);
%
% Generate truth signals
%
% Input:
% seed: random number seed (allows it to generate repeatable results)
%
% Output:
% T: truth struct with fields...
% L: actual levels
www.eeworm.com/read/253623/12209056
m truth.m
function T = truth(seed);
%
% Generate truth signals
%
% Input:
% seed: random number seed (allows it to generate repeatable results)
%
% Output:
% T: truth struct with fields...
% L: actual levels
www.eeworm.com/read/150905/12249320
m nlfisherm.m
%NLFISHERM Non-linear Fisher Mapping according to Marco Loog
%
% W = NLFISHERM(A,N)
%
% INPUT
% A Dataset
% N Number of dimensions (optional; default: MIN(K,C)-1, where
% K is the di
www.eeworm.com/read/149739/12353594
m nlfisherm.m
%NLFISHERM Non-linear Fisher Mapping according to Marco Loog
%
% W = NLFISHERM(A,N)
%
% INPUT
% A Dataset
% N Number of dimensions (optional; default: MIN(K,C)-1, where
% K is the di
www.eeworm.com/read/148768/12427253
m truth.m
function T = truth(seed);
%
% Generate truth signals
%
% Input:
% seed: random number seed (allows it to generate repeatable results)
%
% Output:
% T: truth struct with fields...
% L: actual levels
www.eeworm.com/read/386050/8768943
m nlfisherm.m
%NLFISHERM Non-linear Fisher Mapping according to Marco Loog
%
% W = NLFISHERM(A,N)
%
% INPUT
% A Dataset
% N Number of dimensions (optional; default: MIN(K,C)-1, where
% K is the di
www.eeworm.com/read/299984/7140540
m nlfisherm.m
%NLFISHERM Non-linear Fisher Mapping according to Marco Loog
%
% W = NLFISHERM(A,N)
%
% INPUT
% A Dataset
% N Number of dimensions (optional; default: MIN(K,C)-1, where
% K is the di
www.eeworm.com/read/460435/7251016
m nlfisherm.m
%NLFISHERM Non-linear Fisher Mapping according to Marco Loog
%
% W = NLFISHERM(A,N)
%
% INPUT
% A Dataset
% N Number of dimensions (optional; default: MIN(K,C)-1, where
% K is the di