MATLAB: How to feed discrete i/p to simulink model

discrete i/p

can any one tell me please how to give a discrete input per cycle to simulink model? i mean i want to give input like 01011 and model should take the input one by one per cycle. So first cycle it should take i/p as 0, next cycle 1, next+1 cycle 0 etc.

Best Answer

Possible with any of the following blocks

Sources\From Workspace
Sources\Repeating Sequence
Sources\Repeating Stair

Related Solutions

MATLAB: How to generate one signal from a vector data in simulink

My understanding if your question is that you want those 10 values to make up one period of a periodic waveform, right?

If so, check out the Repeating Sequence block: http://www.mathworks.com/help/simulink/slref/repeatingsequence.html

The block above generates a continuous-time signal so you have to also specify time values. There are also "Repeating Sequence Interpolated" and "Repeating Sequence Stair" blocks that may better meet your needs.

- Sebastian

MATLAB: Processing of i/p data

Hi Hoda,

It is generally considered a good practice to pre and post process the data before and after its handled by the network. And that is what the NN toolbox does by default.

The available methods for pre processing inputs and post processing outputs can be access in a 2-layer network by typing:

net.inputs{1}.processFcns 
net.outputs{2}.processFcns

So, you won't have to do anything at all. The network will receive your inputs and normalize them using mapminmax. Then the data will be processed by the network and then the outputs will be transformed back to your original units.

An example to make the math more clear:

load cancer_dataset;
% Creating a 2-layer Feed-forward network
mlp_net = newff(cancerInputs,cancerTargets,2,{'tansig'},'trainlm');
% Training the network
[mlp_net,tr] = train(mlp_net,cancerInputs,cancerTargets);
% New input to be simulated
p = 10*rand(9,1);
% The network is using mapminmax under the hood
y0 = sim(mlp_net,p);
% Now, let's do it manually to see if we obtain the same results:
p2 = mapminmax('apply',p,mlp_net.inputs{1}.processSettings{3});
y1 = purelin(mlp_net.lw{2,1}*tansig(mlp_net.iw{1,1}*p2+mlp_net.b{1,1})+mlp_net.b{2,1});
y2 = mapminmax('reverse',y1,mlp_net.outputs{2}.processSettings{2});
>> isequal(y0,y2)
ans =
       1

Again, if you are using MATLAB R2011a, feedforwardnet is more efficient than newff. Just wanted to make sure that you can run the code no matter what version you have.

Best Answer

Related Solutions

MATLAB: How to generate one signal from a vector data in simulink

MATLAB: Processing of i/p data

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