Adaptive signal processing
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Learning feed-forward and recurrent fuzzy systems: a genetic approach
Journal of Systems Architecture: the EUROMICRO Journal - Special issue on evolutionary computing
Approximation of dynamic systems using recurrent neuro-fuzzy techniques
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A learning algorithm for continually running fully recurrent neural networks
Neural Computation
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
Identification and control of dynamic systems using recurrent fuzzy neural networks
IEEE Transactions on Fuzzy Systems
Noisy speech processing by recurrently adaptive fuzzy filters
IEEE Transactions on Fuzzy Systems
A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Takagi-Sugeno fuzzy modeling incorporating input variables selection
IEEE Transactions on Fuzzy Systems
Structure identification of generalized adaptive neuro-fuzzy inference systems
IEEE Transactions on Fuzzy Systems
Fuzzy adaptive filters, with application to nonlinear channel equalization
IEEE Transactions on Fuzzy Systems
Modeling and control of carbon monoxide concentration using a neuro-fuzzy technique
IEEE Transactions on Fuzzy Systems
Recurrent neuro-fuzzy networks for nonlinear process modeling
IEEE Transactions on Neural Networks
A recurrent self-organizing neural fuzzy inference network
IEEE Transactions on Neural Networks
Generalization of adaptive neuro-fuzzy inference systems
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Locally recurrent globally feedforward networks: a critical review of architectures
IEEE Transactions on Neural Networks
Memory neuron networks for identification and control of dynamical systems
IEEE Transactions on Neural Networks
Diagonal recurrent neural networks for dynamic systems control
IEEE Transactions on Neural Networks
Fuzzy neural network structure identification based on soft competitive learning
International Journal of Hybrid Intelligent Systems
A fuzzy-neural multi-model for nonlinear systems identification and control
Fuzzy Sets and Systems
Dynamic programming prediction errors of recurrent neural fuzzy networks for speech recognition
Expert Systems with Applications: An International Journal
A recurrent self-evolving interval type-2 fuzzy neural network for dynamic system processing
IEEE Transactions on Fuzzy Systems
A locally recurrent fuzzy neural network with support vector regression for dynamic-system modeling
IEEE Transactions on Fuzzy Systems
Qualitative modeling of dynamical systems employing continuous-time recurrent fuzzy systems
Fuzzy Sets and Systems
Recurrent fuzzy system design using elite-guided continuous ant colony optimization
Applied Soft Computing
Modeling with discrete-time recurrent fuzzy systems via mixed-integer optimization
Fuzzy Sets and Systems
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A high-order recurrent neuro-fuzzy system (HO-RNFS) is suggested in this paper, suitable for modeling highly complex nonlinear temporal processes. Feedback connections are introduced in the network including the context and the feedback nodes that serve as a means to memorize the firing history. The feedback paths in the firing loop are implemented through finite impulse response (FIR) synaptic filters leading to a higher-order network with enhanced temporal capabilities. The inference mechanism of the HO-RNFS is implemented by means of dynamic fuzzy rules where multiple steps-ahead predictions are provided for the internal variables, at the consequent part. Its structure is organized in an on-line fashion using a concurrent structure and parameter algorithm. Structure learning generates dynamically the input and output clusters of the rules, while parameter learning adjusts the network weights. The HO-RNFS is compared to the recurrent self-organizing neural fuzzy inference network (RSONFIN), being a special case of the suggested network. The experimental setup includes a benchmark temporal system and the adaptive noise cancellation problem. Extensive experimentation reveals that HO-RNFS exhibits superior speech enhancement performance as contrasted to RSONFIN, when complex noise passages are considered.