Elementary Function Generators for Neural-Network Emulators  

Oleh:

Vassiliadis, S. ; Zhang, Ming ; Delgado-Frias, J. G.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 6 (2000), page 1438-1449.
Topik: emulator; elementary function; generators; neural - network; emulators

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Piecewise first - and second - order approximations are employed to design commonly used elementary function generators for neural - network emulators. Three novel schemes are proposed for the first - order approximations. The first scheme requires one multiplication, one addition, and a 28 - byte lookup table. The second scheme requires one addition, a 14 - byte lookup table, and no multiplication. The third scheme needs a 16 - byte lookup table, no multiplication, and no addition. A second - order approximation approach provides better function precision ; it requires more hardware and involves the computation of one multiplication and two additions and access to a 28 - byte lookup table. We consider bit serial implementations of the schemes to reduce the hardware cost. The maximum delay for the four schemes ranges from 24 - to 32 - bit serial machine cycles ; the second - order approximation approach has the largest delay. The proposed approach can be applied to compute other elementary function with proper considerations.

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