Phase Oscillatory Network and Visual Pattern Recognition

• Published in: IEEE transaction on neural networks and learning systems Vol. 26; no. 7; pp. 1539 - 1544
• Main Authors: Follmann, Rosangela, Macau, Elbert E. N., Rosa, Epaminondas, Piqueira, Jose R. C.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Associative memory; Color; Couplings; Eigenvalues and eigenfunctions; Electronic Data Processing - methods; Fourier Analysis; information processing; Information retrieval; Information Storage and Retrieval; Memory; Neural Networks, Computer; Neurons; Oscillators; Pattern recognition; Pattern Recognition, Automated - methods; phase oscillator; Reproducibility of Results; synchronization; Visualization; information processing; Associative memory; synchronization; phase oscillator
• ISSN: 2162-237X; 2162-2388; 2162-2388
• DOI: 10.1109/TNNLS.2014.2345572

We explore a properly interconnected set of Kuramoto type oscillators that results in a new associative-memory network configuration, which includes second- and third-order additional terms in the Fourier expansion of the network's coupling. Investigation of the response of the network to different external stimuli indicates an increase in the network capability for coding and information retrieval. Comparison of the network output with that of an equivalent experiment with subjects, for recognizing perturbed binary patterns, shows comparable results between the two approaches. We also discuss the enhanced storage capacity of the network.