Journal ArticleDOI
Nonlinear Systems Modeling Based on Self-Organizing Fuzzy-Neural-Network With Adaptive Computation Algorithm
TLDR
A self-organizing fuzzy-neural-network with adaptive computation algorithm (SOFNN-ACA) that incorporates an adaptive learning rate strategy into the learning process to accelerate the convergence speed and is used to model nonlinear systems.Abstract:
In this paper, a self-organizing fuzzy-neural-network with adaptive computation algorithm (SOFNN-ACA) is proposed for modeling a class of nonlinear systems. This SOFNN-ACA is constructed online via simultaneous structure and parameter learning processes. In structure learning, a set of fuzzy rules can be self-designed using an information-theoretic methodology. The fuzzy rules with high spiking intensities (SI) are divided into new ones. And the fuzzy rules with a small relative mutual information (RMI) value will be pruned in order to simplify the FNN structure. In parameter learning, the consequent part parameters are learned through the use of an ACA that incorporates an adaptive learning rate strategy into the learning process to accelerate the convergence speed. Then, the convergence of SOFNN-ACA is analyzed. Finally, the proposed SOFNN-ACA is used to model nonlinear systems. The modeling results demonstrate that this proposed SOFNN-ACA can model nonlinear systems effectively.read more
Citations
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Journal ArticleDOI
Study on Self-Tuning Tyre Friction Control for Developing Main-Servo Loop Integrated Chassis Control System
TL;DR: A self-tuning longitudinal slip ratio controller (LSC) based on the nonsingular and fast terminal sliding mode (NFTSM) control method is designed to improve the tracking accuracy and response speed of the actuators and the proposed integrated chassis control strategies are verified by computer simulations.
Journal ArticleDOI
Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System
TL;DR: Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.
Journal ArticleDOI
Recent advances in neuro-fuzzy system: A survey
K V Shihabudheen,G. N. Pillai +1 more
TL;DR: A review of different neuro-fuzzy systems based on the classification of research articles from 2000 to 2017 is proposed to help readers have a general overview of the state-of-the-arts of neuro- fizzy systems and easily refer suitable methods according to their research interests.
Journal ArticleDOI
Automatic Facial Expression Recognition System Using Deep Network-Based Data Fusion
TL;DR: Simulation results validate that the proposed AFERS is more efficient as compared to the existing approaches and the recognition results obtained from fused features are found to be distinctly superior to both recognition using individual features as well as recognition with a direct concatenation of the individual feature vectors.
Journal ArticleDOI
An Incremental Learning of Concept Drifts Using Evolving Type-2 Recurrent Fuzzy Neural Networks
TL;DR: The eT2RFNN adopts a holistic concept of evolving systems, where the fuzzy rule can be automatically generated, pruned, merged, and recalled in the single-pass learning mode, and is capable of coping with the problem of high dimensionality because it is equipped with online feature selection technology.
References
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