Abstract
In the present article, we extend the theory of exponential sampling type neural network operators to the max-product setting. The approximation properties of these operators activated by the sigmoidal functions have been studied by using the moment type approach. We establish the point-wise and uniform approximation theorem for these operators along with the quantitative estimate of the order of convergence using the modulus of continuity. Consequently, we discuss the convergence of exponential sampling type quasi-interpolation operators of the max-product kind. At the end, we provide a few examples of the sigmoidal functions satisfying the assumptions of the presented theory.
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