Neural Networks As Positive Linear Operators

Name: Neural Networks As Positive Linear Operators
Price: 345.06 AUD
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ISBN: 9789819826186

George A Anastassiou (The University Of Memphis, Usa)

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English

World Scientific Publishing Co Pte Ltd
13 April 2026

Functional analysis & transforms; Maths for computer scientists

Series: Series on Concrete & Applicable Mathematics

Summary
Details

This research monograph presents a groundbreaking unification of neural network approximation theory through the lens of Positive Linear Operators (PLOs). For the first time in the literature, neural network operators and activated convolution operators are rigorously analyzed as PLOs — providing a comprehensive, quantitative framework based on inequalities and the modulus of continuity.

The author develops a general, elegant, and highly versatile theory that applies uniformly to a wide variety of neural and convolution operators, bridging Pure and Applied Mathematics with modern Artificial Intelligence and Machine Learning. The results open new directions for mathematical understanding of neural network approximation, with applications across computational analysis, engineering, statistics, and economics.

This volume is an essential resource for mathematicians, computer scientists, and engineers seeking a rigorous analytical foundation for AI and deep learning models.

By: George A Anastassiou (The University Of Memphis Usa)
Imprint: World Scientific Publishing Co Pte Ltd
Country of Publication: Singapore
Volume: 28
ISBN: 9789819826186
ISBN 10: 9819826187
Series: Series on Concrete & Applicable Mathematics
Pages: 420
Publication Date: 13 April 2026
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Forthcoming