datafordescr.m

% Let's generate a bunch of deer data for descramblement
% Load the training set parameters
parameters=library_dd();

% Specify number of traces to produce
% parameters.ntraces=1e6;
parameters.training_input = 'noisy_deer'; 

% Set the training database name
file_name='example_set.mat';

% % Generate the training library
% [time_grid,dist_grid,dist_distr_lib,...
%     deer_ffact_lib,background_lib,deer_trace_lib,...
%     deer_clean_lib,exchange_lib,parameters]=deer_lib_gen(file_name,parameters);

% sample = deer_lib_gen(file_name,parameters);

% train one net using parameters
train_one_net(parameters, 1e6, 1010101)