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Ultimate mean square boundedness (Levinson dissipativity) conditions for the designed closed loop system are obtained; it is shown that, in some special cases, the dissipativity of the closed loop system is preserved under white noise perturbations of arbitrary intensity.
Similar(59)
It has been observed that the neural network was having 6 neurons in input, 20 neurons in 1st hidden layer, 20 neurons in 2nd hidden layer and 1 neuron in output layer all comprising of "tansig" activation function for ANN based fault detector (6-20-20-2) can able to minimize the mean square error (mse) to an ultimate value of 0.00000989.
The ultimate choice for the model is made based on the goodness of fit criteria such as the least residual mean square error and Akaike Information Criteria.
Rood mean square (r.m.s).
minimum mean square estimate.
root mean square deviation.
Root mean square.
mean square weight.
Normalised mean square error.
Root mean square approximation.
Excess mean square error.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com