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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| creator | Citko, W. Sienko, W. |
| description | 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. |
| doi_str_mv | 10.1109/INDS.2009.5227991 |
| format | Conference Proceeding |
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The machine learning techniques has been used as the analytical tool.</abstract><pub>IEEE</pub><doi>10.1109/INDS.2009.5227991</doi><tpages>4</tpages></addata></record> |
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| ispartof | 2009 2nd International Workshop on Nonlinear Dynamics and Synchronization, 2009, p.209-212 |
| issn | 2324-8297 |
| language | eng |
| recordid | cdi_ieee_primary_5227991 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Approximation methods Associative memory design of associative memories Filters Hilbert space Kernel Large-scale systems Machine learning Neural networks Neurofeedback Nonlinear equations nonlinear mappings |
| title | Design of associative memories by using machine learning |
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