Delay probability in adaptive systems based on activation function of classical neural networks

IF 5 3区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Egyptian Informatics Journal Pub Date : 2024-10-14 DOI:10.1016/j.eij.2024.100555
Maja Lutovac Banduka , Vladimir Mladenović , Danijela Milosević , Vladimir Orlić , Asutosh Kar
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引用次数: 0

Abstract

Many improved algorithms have been proposed for nonlinear system designs. There is no single procedure for providing an algorithm with closed-form system response relations as a function of system parameters. In this paper, we illustrate a unique method for discrete-time digital nonlinear systems. Provides better insight into the analyzed system, algorithm, and processes. The main contribution is closed-form symbolic responses in the time domain and modifications of the implemented algorithm. A comparison of adaptive systems and neural networks is also presented. The design and analysis of nonlinear systems are more clearly simplified for either engineers or researchers without deep mathematical knowledge.
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基于经典神经网络激活函数的自适应系统中的延迟概率
针对非线性系统设计提出了许多改进算法。目前还没有一种算法能提供与系统参数有关的闭式系统响应关系。在本文中,我们阐述了一种适用于离散时间数字非线性系统的独特方法。它能让我们更好地了解所分析的系统、算法和过程。主要贡献在于时域的闭式符号响应和对已实施算法的修改。此外,还对自适应系统和神经网络进行了比较。对于没有深厚数学知识的工程师或研究人员来说,非线性系统的设计和分析得到了更清晰的简化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Egyptian Informatics Journal
Egyptian Informatics Journal Decision Sciences-Management Science and Operations Research
CiteScore
11.10
自引率
1.90%
发文量
59
审稿时长
110 days
期刊介绍: The Egyptian Informatics Journal is published by the Faculty of Computers and Artificial Intelligence, Cairo University. This Journal provides a forum for the state-of-the-art research and development in the fields of computing, including computer sciences, information technologies, information systems, operations research and decision support. Innovative and not-previously-published work in subjects covered by the Journal is encouraged to be submitted, whether from academic, research or commercial sources.
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