[HTML][HTML] Random vector functional link network: recent developments, applications, and future directions
Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …
classification, regression and clustering, etc. Generally, the back propagation (BP) based …
A comprehensive review for industrial applicability of artificial neural networks
This paper presents a comprehensive review of the industrial applications of artificial neural
networks (ANNs), in the last 12 years. Common questions that arise to practitioners and …
networks (ANNs), in the last 12 years. Common questions that arise to practitioners and …
Deep learning for time-series analysis
JCB Gamboa - ar** in data-scarce urban areas
Floods are natural hazards with potentially huge consequences on the environment,
economy, and human life and property. Therefore, emerging engineering approaches, such …
economy, and human life and property. Therefore, emerging engineering approaches, such …
Data fusion and sensor integration: State-of-the-art 1990s
RC Luo, MG Kay - Data fusion in robotics and machine …, 1992 - books.google.com
The synergistic use of multiple sensors by machines and systems is a major factor in
enabling some measure of intelligence to be incorporated into their overall operation so that …
enabling some measure of intelligence to be incorporated into their overall operation so that …
Artificial neural networks for pattern recognition
B Yegnanarayana - Sadhana, 1994 - Springer
This tutorial article deals with the basics of artificial neural networks (ANN) and their
applications in pattern recognition. ANN can be viewed as computing models inspired by the …
applications in pattern recognition. ANN can be viewed as computing models inspired by the …
An orthogonal neural network for function approximation
SS Yang, CS Tseng - IEEE Transactions on Systems, Man, and …, 1996 - ieeexplore.ieee.org
This paper presents a new single-layer neural network which is based on orthogonal
functions. This neural network is developed to avoid the problems of traditional feedforward …
functions. This neural network is developed to avoid the problems of traditional feedforward …
An approach to stability criteria of neural-network control systems
K Tanaka - IEEE Transactions on Neural Networks, 1996 - ieeexplore.ieee.org
This paper discusses stability of neural network (NN)-based control systems using Lyapunov
approach. First, it is pointed out that the dynamics of NN systems can be represented by a …
approach. First, it is pointed out that the dynamics of NN systems can be represented by a …
Stability and stabilizability of fuzzy-neural-linear control systems
K Tanaka - IEEE Transactions on Fuzzy Systems, 1995 - ieeexplore.ieee.org
This paper discusses stability analysis of fuzzy-neural-linear (FNL) control systems which
consist of combinations of fuzzy models, neural network (NN) models, and linear models …
consist of combinations of fuzzy models, neural network (NN) models, and linear models …