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Article

Approximation by Overactivated and Spiked Convolutions as Positive Linear Operators

by
George A. Anastassiou
Department of Mathematical Sciences, University of Memphis, Memphis, TN 38152, USA
Mathematics 2025, 13(24), 4033; https://doi.org/10.3390/math13244033
Submission received: 25 November 2025 / Revised: 13 December 2025 / Accepted: 17 December 2025 / Published: 18 December 2025

Abstract

In this work, the author studied the quantitative approximation to the unit operator of three kinds of overactivated and spiked convolution type-operators. These operators have as a kernel a cusp coming from a constructed S-shaped finite-length arc, serving as a new activation function of compact support. This is derived from the composition of two general sigmoid activation functions with domain all reals. Our operators are positive linear ones and are treated as such. Initially we establish the basic convergence, then we move on to simultaneous and iterated approximations, all via inequalities and involving the modulus of continuity of the approximated univariate function.
Keywords: overactivated neural networks; spiked neural networks; convolution; quantitative approximation; simultaneous; iterated approximation overactivated neural networks; spiked neural networks; convolution; quantitative approximation; simultaneous; iterated approximation

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MDPI and ACS Style

Anastassiou, G.A. Approximation by Overactivated and Spiked Convolutions as Positive Linear Operators. Mathematics 2025, 13, 4033. https://doi.org/10.3390/math13244033

AMA Style

Anastassiou GA. Approximation by Overactivated and Spiked Convolutions as Positive Linear Operators. Mathematics. 2025; 13(24):4033. https://doi.org/10.3390/math13244033

Chicago/Turabian Style

Anastassiou, George A. 2025. "Approximation by Overactivated and Spiked Convolutions as Positive Linear Operators" Mathematics 13, no. 24: 4033. https://doi.org/10.3390/math13244033

APA Style

Anastassiou, G. A. (2025). Approximation by Overactivated and Spiked Convolutions as Positive Linear Operators. Mathematics, 13(24), 4033. https://doi.org/10.3390/math13244033

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