% Tutorial: generat compact_Data using function gen_cmpct_Data.p

>>sysc=[tf(1,[1 1]), tf(2,[10 1]);tf(1,[5 1],'inputdelay',2), tf(3,[8 1],'inputdelay',1)];  % generate continuous TF
>>sysd=c2d(sysc,1); % try discrete TF. Note MVPA can take both continuous TF and discrete TF
>>y=randn(100,2); % generate output data randomly
% Now we are ready to run the compact data generator
>>gen_cmpct_Data
 
Consider a process with m inputs and p outputs
 
1. Plant model (continuous/discrete): p x m tf matrix
2. Output data (y): N x p matrix
3. Sampling time
 
Continuous/discrete transfer function matrix: sysc  % try continuous TF
Output data matrix: y
Sampling time: 1
The file name to save compact data (e.g. test_cmpct_data): test_cmpct_data_con
The file name to save plant model (e.g. test_model): test_model_con
% we have generated data/model to run MVPA. Next we generate another set of data/model using discrete TF
>>gen_cmpct_Data
 
Consider a process with m inputs and p outputs
 
1. Plant model (continuous/discrete): p x m tf matrix
2. Output data (y): N x p matrix
3. Sampling time
 
Continuous/discrete transfer function matrix: sysd % try discrete TF
Output data matrix: y
Sampling time: 1
The file name to save compact data (e.g. test_cmpct_data): test_cmpct_data_dis
The file name to save plant model (e.g. test_model): test_model_dis
% We have generated two sets of data/models to run MVPA. Either one can be used to run MVPA and the results should be same
% Next type main_mvpa to run MVPA in the directory containing MVPA