som_settings.m

MOLMAP multiway toolbox是一个matlab集成工具箱

function settings = som_settings(type)

% default setting structure 
% som_settings build a default structure 
% 
% settings = som_settings(type);
%
% input:
%   type        type of settings ('multiway')
% 
% output:
%   settings is a structure, with the following fields
%       settings.nsize          net size (default = NaN)
%       settings.epochs         number of total epochs (default = NaN)
%       settings.bound          boundary condition ('toroidal' or 'normal', defualt = 'toroidal')
%       settings.enter          entering mode of samples ('random' or 'sequential', defualt = 'random')
%       settings.a_max          initial learning rate, defualt = 0.5
%       settings.a_min          final learning rate, defualt = 0.01
%       settings.a_chg          learning rate proportional to epochs ('to_epo') or epochs*samples ('to_epoobj'), defualt = 'to_epo'
% 
% see the HTML HELP files (help.htm) for extensive explanations, details and examples
%
% The toolbox is freeware and may be used (but not modified) 
% if proper reference is given to the authors. Preferably refer to:
% D. Ballabio, V. Consonni, R. Todeschini
% Classification of multiway analytical data based on MOLMAP approach
% Analytica Chimica Acta, in press
%
% version 1.0 - november 2007
% Davide Ballabio
% Milano Chemometrics and QSAR Research Group
% www.disat.unimib.it/chm


settings         = [];
settings.name    = ['som_settings_' type];
settings.nsize   = NaN;          % net size
settings.epochs  = NaN;          % number of total epochs
settings.bound   = 'toroidal';   % boundary condition ('toroidal' or 'normal')
settings.enter   = 'random';     % entering mode of samples ('random' or 'sequential')
settings.a_max   = 0.5;          % initial learning rate
settings.a_min   = 0.01;         % final learning rate
settings.a_chg   = 'to_epo';     % learning rate linear decreasing proportional to epochs ('to_epo') or epochs*samples ('to_epoobj')