1. Are Neural Fields Suitable for Vector Quantization?
- Author
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Lucian Alecu, Hervé Frezza-Buet, Neuromimetic intelligence (CORTEX), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP), SUPELEC-Campus Metz, Ecole Supérieure d'Electricité - SUPELEC (FRANCE), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Theoretical computer science ,Group method of data handling ,Computer science ,Perspective (graphical) ,Vector quantization ,02 engineering and technology ,[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] ,Measure (mathematics) ,Field (computer science) ,03 medical and health sciences ,Kernel (linear algebra) ,0302 clinical medicine ,Character (mathematics) ,0202 electrical engineering, electronic engineering, information engineering ,Benchmark (computing) ,020201 artificial intelligence & image processing ,030217 neurology & neurosurgery - Abstract
International audience; This paper focuses on the possibility of enabling vector quantization learning techniques into dynamic neural fields, as an attempt to enrich their usage in bio-inspired applications. As mathematical approaches prove rather difficult to propose a practical solution, due to the non-linear character of the field equations, we adopt a different perspective in order to deal with this problem. This consists in simulating the evolution of the field and design an empirical method able to measure its quality. The developed benchmark framework implementing this approach is used to check whether a given field is capable to behave as expected in various situations, in particular those involving self-organization by vector quantization.
- Published
- 2008
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