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Titlebook: Ordinary and Fractional Approximation by Non-additive Integrals: Choquet, Shilkret and Sugeno Integr; George A. Anastassiou Book 2019 Spri

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51#
發(fā)表于 2025-3-30 11:45:22 | 只看該作者
George A. Anastassiouencers to foster and sustain their influence, marking the fourth dimension of the model under scrutiny. The chapter unravels the thoughtful choices micro-influencers make concerning their content publishing, sharing, and networking within their social media platforms. Additionally, it also emphasise
52#
發(fā)表于 2025-3-30 14:25:55 | 只看該作者
53#
發(fā)表于 2025-3-30 20:05:55 | 只看該作者
54#
發(fā)表于 2025-3-30 23:08:10 | 只看該作者
George A. Anastassioung models, the processing of the data can sometimes prove to be the most important step in the data pipeline. In this work, we collect kernel-level system calls on a resource-constrained Internet of Things (IoT) device, apply lightweight Natural Language Processing (NLP) techniques to the data, and
55#
發(fā)表于 2025-3-31 04:15:08 | 只看該作者
56#
發(fā)表于 2025-3-31 07:02:24 | 只看該作者
57#
發(fā)表于 2025-3-31 09:10:44 | 只看該作者
,Approximation with Rates by Perturbed Kantorovich–Choquet Neural Network Operators,ed neural network operators of one hidden layer. These are given through the univariate and multivariate moduli of continuity of the involved univariate or multivariate function or its high order derivatives and that appears in the right-hand side of the associated univariate and multivariate Jackso
58#
發(fā)表于 2025-3-31 13:20:28 | 只看該作者
59#
發(fā)表于 2025-3-31 20:06:26 | 只看該作者
Approximation with Rates by Shift Invariant Multivariate Sublinear-Choquet Operators,neral positive sublinear operator with a multivariate scaling type function. For it sufficient conditions are given for shift invariance, preservation of global smoothness, convergence to the unit with rates. Furthermore, two examples of very general multivariate specialized operators are presented
60#
發(fā)表于 2025-4-1 00:44:13 | 只看該作者
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