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The new controller of adaptive neural network with state feedback is presented by using a universal approximation of radial basis function neural network and backstepping.
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Mathematical modeling of SP-BVPs is constructed by using a universal function approximation capability of ANNs in mean square sense.
Micro-shear testing was performed using a universal testing machine.
The mechanical testing was performed using a universal testing machine.
Ligated products were amplified using a universal primer set.
Using the universal approximation capability of the fuzzy system, we construct a fuzzy system as the upper bound of uncertainties in the nonlinear uncertain system.
Confidence intervals were calculated using a normality approximation algorithm.
Confidence intervals (CI) were calculated using a normality approximation algorithm.
The model was fitted using a Laplacian approximation.
The author does so by using a common approximation in OR: he reduces the number of equations to a finite number using the geometric tail approximation.
They can be used to extrapolate the intensity values to #mm>2 in a rough approximation.
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