Pattern Discovery for High-Dimensional Binary Datasets
Neural Information Processing
Implementing Boolean Matrix Factorization
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Factor Analysis of Incidence Data via Novel Decomposition of Matrices
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Discovery of optimal factors in binary data via a novel method of matrix decomposition
Journal of Computer and System Sciences
Analysis of continuous attractors for 2-D linear threshold neural networks
IEEE Transactions on Neural Networks
Recurrent-neural-network-based Boolean factor analysis and its application to word clustering
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Nontrivial global attractors in 2-D multistable attractor neural networks
IEEE Transactions on Neural Networks
Bars problem solving - new neural network method and comparison
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Computing the lattice of all fixpoints of a fuzzy closure operator
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Factorizing three-way binary data with triadic formal concepts
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Neural network Boolean factor analysis and application
CIMMACS'07 Proceedings of the 6th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
New measure of boolean factor analysis quality
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
Structural design of optimized polynomial radial basis function neural networks
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Neural networks algorithm based on factor analysis
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Attractor neural network combined with likelihood maximization algorithm for boolean factor analysis
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Context FCM-based radial basis function neural networks with the aid of fuzzy clustering
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
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A common problem encountered in disciplines such as statistics, data analysis, signal processing, textual data representation, and neural network research, is finding a suitable representation of the data in the lower dimension space. One of the principles used for this reason is a factor analysis. In this paper, we show that Hebbian learning and a Hopfield-like neural network could be used for a natural procedure for Boolean factor analysis. To ensure efficient Boolean factor analysis, we propose our original modification not only of Hopfield network architecture but also its dynamics as well. In this paper, we describe neural network implementation of the Boolean factor analysis method. We show the advantages of our Hopfield-like network modification step by step on artificially generated data. At the end, we show the efficiency of the method on artificial data containing a known list of factors. Our approach has the advantage of being able to analyze very large data sets while preserving the nature of the data