How to read result of sim using Patternnet ?

To read and interpret the results of a neural network simulation using `patternnet` in MATLAB, follow these steps:

1. Train the Patternnet:
   First, you need to train your `patternnet` with your input data and target data.

    
    % Example data
    x = rand(10, 100);  % 10 features, 100 samples
    t = rand(1, 100);   % 1 target, 100 samples
    
    % Create the network
    net = patternnet(10);  % 10 hidden neurons
    
    % Train the network
    net = train(net, x, t);
    

2. *Simulate the Network:
   Use the trained network to simulate and obtain outputs for new input data.

   
    % New input data for simulation
    new_x = rand(10, 50);  % 10 features, 50 samples
    
    % Simulate the network
    y = net(new_x);
    

3. Interpret the Results:
   The result `y` is the output of the network. Depending on your problem, you may need to interpret these results accordingly.

    matlab
    % Display the results
    disp(y);
    

4. Analyze the Performance:
   Optionally, you can evaluate the performance of your network using appropriate metrics.

    
    % Performance evaluation
    performance = perform(net, t, y);
    disp(['Performance: ', num2str(performance)]);
    

This process involves training the `patternnet` with your data, simulating it with new inputs, and then interpreting the output results.