Exploiting Application Locality to Design Low-Complexity, Highly Performing, and Power-Aware Embedded Classifiers  

Oleh:

Alippi, C. ; Scotti, F.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 17 no. 3 (May 2006), page 745-754.
Topik: DESIGN; application; locality; design low - complexity; highly performing; power - aware embedded; classifiers

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Temporal and spatial locality of the inputs, i. e., the property allowing a classifier to receive the same samples over time - or samples belonging to a neighborhood - with high probability, can be translated into the design of embedded classifiers. The outcome is a computational complexity and power aware design particularly suitable for implementation. A classifier based on the gated - parallel family has been found particularly suitable for exploiting locality properties : Subclassifiers are generally small, independent each other, and controlled by a master - enabling module granting that only a subclassifier is active at a time, the others being switched off. By exploiting locality properties we obtain classifiers with accuracy comparable with the ones designed without integrating locality but gaining a significant reduction in computational complexity and power consumption.

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