## On the approximation by single hidden layer feedforward neural networks with fixed weights

*Guliyev , Namig ,*;

*Ismailov , Vugar ,*;

- Publisher: Elsevier
Related identifiers: - Subject: activation function | sigmoidal function | approximation | ACM : I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning/I.2.6.2: Connectionism and neural nets | C.1.3 | ACM : I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.3: Neural nets | [ MATH.MATH-NA ] Mathematics [math]/Numerical Analysis [math.NA] | I.2.6 | weight | [ INFO.INFO-NE ] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] | I.5.1 | [ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT] | feedforward neural network | Computer Science - Information Theory | hidden layer | [ MATH.MATH-IT ] Mathematics [math]/Information Theory [math.IT] | 2010 MSC: 41A30, 41A63, 65D15, 68T05, 92B20 | Computer Science - Neural and Evolutionary Computing | ACM : C.: Computer Systems Organization/C.1: PROCESSOR ARCHITECTURES/C.1.3: Other Architecture Styles/C.1.3.7: Neural nets | Mathematics - Numerical Analysis | 41A30, 41A63, 65D15, 68T05, 92B20 | ACM : F.: Theory of Computation/F.1: COMPUTATION BY ABSTRACT DEVICES/F.1.1: Models of Computation/F.1.1.4: Self-modifying machines (e.g., neural networks) | F.1.1arxiv: Quantitative Biology::Neurons and Cognition

International audience; Feedforward neural networks have wide applicability in various disciplines of science due to their universal approximation property. Some authors have shown that single hidden layer feedforward neural networks (SLFNs) with fixed weights still pos... View more

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