DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction
- N. Kasabov, Q. Song
- Computer ScienceIEEE transactions on fuzzy systems
- 1 April 2002
It is demonstrated that DENFIS can effectively learn complex temporal sequences in an adaptive way and outperform some well-known, existing models.
Foundations Of Neural Networks, Fuzzy Systems, And Knowledge Engineering [Books in Brief]
- N. Kasabov
- Computer ScienceIEEE Transactions on Neural Networks
- 11 October 1996
Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning
- N. Kasabov
- Computer ScienceIEEE Trans. Syst. Man Cybern. Part B
- 1 December 2001
This paper introduces evolving fuzzy neural networks (EFuNNs) as a means for the implementation of the evolving connectionist systems (ECOS) paradigm that is aimed at building online, adaptive…
Evolving Connectionist Systems: The Knowledge Engineering Approach
- N. Kasabov
- Computer Science, Biology
- 23 August 2007
Evolving Connectionist Methods for Unsupervised Learning, Feature Selection, Model Creation, and Model Validation and Brain Inspired Evolving Connectionist Models.
Incremental linear discriminant analysis for classification of data streams
- Shaoning Pang, S. Ozawa, N. Kasabov
- Computer ScienceIEEE Transactions on Systems, Man, and…
- 1 October 2005
The results show that the proposed ILDA can effectively evolve a discriminant eigenspace over a fast and large data stream, and extract features with superior discriminability in classification, when compared with other methods.
Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines
- N. Kasabov
- Computer Science, BiologyIEEE Transactions on Neural Networks
- 1 October 2002
This chapter discusses the evolution of connectionist systems, which have applications in Bioinformatics, Brain Study and Intelligent Systems, and dynamic Modelling of Brain Functions and Cognitive Processes.
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
- N. Kasabov
- Computer ScienceNeural Networks
- 1 April 2014
HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems
- Jaesoo Kim, N. Kasabov
- Computer ScienceNeural Networks
- 1 November 1999
Evolving Intelligent Systems: Methodology and Applications
- P. Angelov, Dimitar Filev, N. Kasabov
- Computer Science
- 22 March 2010
Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.
Span: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns
- Ammar Mohemmed, S. Schliebs, S. Matsuda, N. Kasabov
- Computer ScienceInternational Journal of Neural Systems
- 25 July 2012
SPAN is presented - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes.
...
...