Design of associative memories by using machine learning

Design of associative memories by using machine learning

Problem of nonlinear mapping-based design of associative memories can be regarded as a covering problem in the case of feedforward architecture and as a generation of fixed points in the case of feedback structure. The machine learning techniques has been used as the analytical tool.

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Bibliographische Detailangaben
Hauptverfasser: Citko, W., Sienko, W.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Approximation methods
Associative memory
design of associative memories
Filters
Hilbert space
Kernel
Large-scale systems
Machine learning
Neural networks
Neurofeedback
Nonlinear equations
nonlinear mappings
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Beschreibung
Zusammenfassung:Problem of nonlinear mapping-based design of associative memories can be regarded as a covering problem in the case of feedforward architecture and as a generation of fixed points in the case of feedback structure. The machine learning techniques has been used as the analytical tool.
ISSN:2324-8297
DOI:10.1109/INDS.2009.5227991