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Consider deep feedforward ANN with its weights and biases, specified in Figure. This ANN has one input layer, two hidden layers and one output layer.
Consider deep feedforward ANN with its weights and biases, specified in Figure. This ANN has one input layer, two hidden layers and one output layer.
For simplicity, assume, that activation function for each node is an identity function, ie a linear function with UNIT coefficient: gxx
For known outputs y; and y and known second and third inputs x x determine the first input x given by the positive or negative integer with absolute value less than this condition can be expressed as follows: x
Figure: Given deep ANN with one input layer, two hidden layers and one output layer.
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