The FPGA-based multi-classifier

被引:0
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作者
Pierre Lorrentz
机构
[1] University of Kent,School of Engineering and Digital Arts
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关键词
Adaptive RLS filters; Weightless FPGA-based EPCN classifier; Neural network fusion; Cognitive system; Weightless neural multi-classifier;
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摘要
To achieve intelligent real-time processing, the paper presents a weightless neural-based cognitive system which is capable of classifying, analysing, and prediction from sight or sound. The proposed cognitive system fused recursive-least-square (RLS) filters in parallel with an enhanced probabilistic convergent network (EPCN) serially—implemented on field programmable gate array. The novelty is that EPCN does not require an optimum result from RLS to achieve good responses from the RLS–EPCN fusion, thereby further offering two main distinguishing features: compactness and speed. Test results demonstrate RLS–EPCN’s suitability to exploration/exploitation of hostile surroundings such as sea exploration.
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页码:207 / 223
页数:16
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