On the theory of flexible neural networks – Part I: a survey paper
DOI10.1080/00207721.2016.1206989zbMath1360.93178OpenAlexW2463753465MaRDI QIDQ2974214
Publication date: 6 April 2017
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2016.1206989
observabilitycontrollabilityminimalityidentifiabilityuniversal approximationfeedforward FNNsrecurrent FNNs
Controllability (93B05) Neural networks for/in biological studies, artificial life and related topics (92B20) System identification (93B30) Research exposition (monographs, survey articles) pertaining to systems and control theory (93-02) Observability (93B07)
Related Items (1)
Cites Work
- State observability in recurrent neural networks
- Using Fourier-neural recurrent networks to fit sequential input/output data
- Complete controllability of continuous-time recurrent neural networks
- On subsystem recognition in compound physical systems
- Matrix measure method for global exponential stability of complex-valued recurrent neural networks with time-varying delays
- Multilayer feedforward networks are universal approximators
- Regularising neural networks using flexible multivariate activation function
- Multilayer perceptrons and radial basis function neural network methods for the solution of differential equations: a survey
- A generic approach to the design of decentralized linear output- feedback controllers
- Introduction to Linear Control Systems
- On the theory of flexible neural networks – Part I: a survey paper
- Universal Approximation by Ridge Computational Models and Neural Networks: A Survey
- Approximation by ridge functions and neural networks with a bounded number of neurons
- Forward accessibility for recurrent neural networks
- Approximation by superpositions of a sigmoidal function
This page was built for publication: On the theory of flexible neural networks – Part I: a survey paper
