| A compact 3D VLSI classifier using bagging threshold network ensembles. | |
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MedLine Citation:
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PMID: 18244563 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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A bagging ensemble consists of a set of classifiers trained independently and combined by a majority vote. Such a combination improves generalization performance but can require large amounts of memory and computation, a serious drawback for addressing portable real-time pattern recognition applications. We report here a compact three-dimensional (3D) multiprecision very large-scale integration (VLSI) implementation of a bagging ensemble. In our circuit, individual classifiers are decision trees implemented as threshold networks - one layer of threshold logic units (TLUs) followed by combinatorial logic functions. The hardware was fabricated using 0.7-/spl mu/m CMOS technology and packaged using MCM-V micro-packaging technology. The 3D chip implements up to 192 TLUs operating at a speed of up to 48 GCPPS and implemented in a volume of (/spl omega/ /spl times/ L /spl times/ h) = (2 /spl times/ 2 /spl times/ 0.7) cm/sup 3/. The 3D circuit features a high level of programmability and flexibility offering the possibility to make an efficient use of the hardware resources in order to reduce the power consumption. Successful operation of the 3D chip for various precisions and ensemble sizes is demonstrated through an electronic nose application. |
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Authors:
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A Bermak; D Martinez |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council Volume: 14 ISSN: 1045-9227 ISO Abbreviation: IEEE Trans Neural Netw Publication Date: 2003 |
Date Detail:
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Created Date: 2008-02-04 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101211035 Medline TA: IEEE Trans Neural Netw Country: United States |
Other Details:
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Languages: eng Pagination: 1097-109 Citation Subset: - |
Affiliation:
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Electr. and Electron. Eng. Dept., Hong Kong Univ. of Sci. and Technol., Kowloon, China. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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