Abstract
Multi-dimensional classification tasks by neural methods are interesting for their performances and their simplicity of operations. However, the number of computations needed by these algorithms is very impressive and drastically limits practical applications of such methods. This paper describes a digital bit-serial, massively parallel associative processor to speed up neural-like classification tasks. To achieve this goal, each block of this associative processor is optimized to the main operations involved in classification algorithms.
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© 1995 Springer-Verlag Berlin Heidelberg
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Thissen, P., Verleysen, M., Legat, JD. (1995). An associative processor dedicated to classification by neural methods. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_241
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DOI: https://doi.org/10.1007/3-540-59497-3_241
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