i am new to matlab and neural networks. i want to train a nn using the condition that are specified. the input is a matrix, and the elements of the output matrix should satisfy specific condition. for eg, the diagonal elements should be zero, the sum of certain elements should be a specified value etc.
also how do i input the matrix. i could only input it as separate rows/columns and not a a whole matrix, whose elements are to be considered together and not individually.
how do i do it using nn toolbox?? should i use the simulink tool boxes??how??
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I think you are confused.
The common Feedforward Multilayer Perceptron either implements regression/curvefitting (fitnet) or classification/pattern-recognition (patternnet).
Given an input matrix of N I-dimensional column vectors, it will output a corresponding matrix of N O-dimensional column vectors.
Each output column corresponds to a single inputcolumn. In matrix notation, y = f(x).
However, there are Time-Series nets where the current output depends on
a. current and past values of input (timedelaynet) y(t) = f(x(t-d: t))
b. past values of output (narnet) y(t) = f(y(t-d: t-1))
c. a combination of a and b (narxnet).
Your description does not seem to fit these scenarios.
Hope this helps.
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