Biologically relevant neural network architectures for support vector machines

DOI10.1016/J.NEUNET.2013.09.006zbMath1296.68131OpenAlexW2143688392WikidataQ50715616 ScholiaQ50715616MaRDI QIDQ461185

Magnus Jändel

Publication date: 10 October 2014

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2013.09.006

zbMATH Keywords

neural networksupport vector machinecompetitive queuing memoryperceptual learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Pattern recognition, speech recognition (68T10)

Cites Work

• Training v-Support Vector Classifiers: Theory and Algorithms
• Odor-Driven Attractor Dynamics in the Antennal Lobe Allow for Simple and Rapid Olfactory Pattern Classification
• Self-organizing maps.
• Approximation by superpositions of a sigmoidal function
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