Speech Communication - Special issue on speech processing in adverse conditions
Minimum Classification Error Training for Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new recurrent neurofuzzy network for identification of dynamic systems
Fuzzy Sets and Systems
Zero-order TSK-type fuzzy system learning using a two-phase swarm intelligence algorithm
Fuzzy Sets and Systems
Fuzzy-rough data reduction with ant colony optimization
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A recurrent self-evolving interval type-2 fuzzy neural network for dynamic system processing
IEEE Transactions on Fuzzy Systems
Modified fuzzy c-means for ordinal valued attributes with particle swarm for optimization
Fuzzy Sets and Systems
On the stability of interval type-2 TSK fuzzy logic control systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
A maximizing-discriminability-based self-organizing fuzzy network for classification problems
IEEE Transactions on Fuzzy Systems
An interval type-2 fuzzy-neural network with support-vector regression for noisy regression problems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Optimization of temporal filters for constructing robust features in speech recognition
IEEE Transactions on Audio, Speech, and Language Processing
A recurrent neural fuzzy network for word boundary detection invariable noise-level environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A recurrent fuzzy-neural model for dynamic system identification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Prediction and identification using wavelet-based recurrent fuzzy neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Dynamic non-Singleton fuzzy logic systems for nonlinear modeling
IEEE Transactions on Fuzzy Systems
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
IEEE Transactions on Fuzzy Systems
Support vector learning for fuzzy rule-based classification systems
IEEE Transactions on Fuzzy Systems
Support vector learning mechanism for fuzzy rule-based modeling: a new approach
IEEE Transactions on Fuzzy Systems
Support-vector-based fuzzy neural network for pattern classification
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A TS-Type Maximizing-Discriminability-Based Recurrent Fuzzy Network for Classification Problems
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
Hierarchical Singleton-Type Recurrent Neural Fuzzy Networks for Noisy Speech Recognition
IEEE Transactions on Neural Networks
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This paper proposes an enhanced discriminability recurrent fuzzy neural network for temporal classification problems. To consider classification problems, the most important consideration is the ''discriminability''. To enhance the ''discriminability'', the feedback topology of the proposed fuzzy neural network is fully connected in order to handle temporal pattern behavior. Furthermore, the proposed fuzzy neural network considers minimum-classification-error and minimum-training-error. In minimum-classification-error, the weights are updated by maximizing the discrimination among different classes. In minimum-training-error, the parameter learning adopts the gradient descent method to reduce the cost function. Therefore, the novelty of the enhanced discriminability recurrent fuzzy neural network is that it not only minimizes the cost function but also maximizes the discriminability. It is constructed from structure and parameter learning. Simulations and comparisons with other recurrent fuzzy neural networks verify the performance of the enhanced discriminability recurrent fuzzy neural network under noisy conditions. Analysis results indicate that the proposed fuzzy neural network exhibits excellent classification performance.