Industrial applications of fuzzy systems
SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
Exponential Transients in Continuous-Time Symmetric Hopfield Nets
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Modeling of the German Yield Curve by Error Correction Neural Networks
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Continuous-time symmetric Hopfield nets are computationally universal
Neural Computation
Data mining tasks and methods: Classification: neural network approaches
Handbook of data mining and knowledge discovery
Abductive reasoning with recurrent neural networks
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
A Complex-Valued RTRL Algorithm for Recurrent Neural Networks
Neural Computation
Applicability of feed-forward and recurrent neural networks to Boolean function complexity modeling
Expert Systems with Applications: An International Journal
Application of neural networks in short-term load forecasting
MMACTE'05 Proceedings of the 7th WSEAS International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering
Dynamic Ridge Polynomial Neural Networks in Exchange Rates Time Series Forecasting
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Extracting symbolic knowledge from recurrent neural networks---A fuzzy logic approach
Fuzzy Sets and Systems
Facial Expression Recognition in Video Sequences
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Spurious valleys in the error surface of recurrent networks: analysis and avoidance
IEEE Transactions on Neural Networks
Behavioural pattern identification and prediction in intelligent environments
Applied Soft Computing
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From the Publisher:With applications ranging from motion detection to financial forecasting, recurrent neural networks (RNNs) have emerged as an interesting and important part of neural network research. Recurrent Neural Networks: Design and Applications reflects the tremendous, worldwide interest in and virtually unlimited potential of RNNs - providing a summary of the design, applications, current research, and challenges of this dynamic and promising field.