Toward A General-Purpose Analog VLSI Neural Network With On-Chip Learning  

Oleh:

Paulos, J. J. ; Montalvo, A. J. ; Gyurcsik, R. S.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 2 (1997), page 413-423.
Topik: analog cellular; general - purpose; analog; VLSI; neural network; on - chip learning

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper describes elements necessary for a general - purpose low - cost very large scale integration (VLSI) neural network. By choosing a learning algorithm that is tolerant of analog nonidealities, the promise of high - density analog VLSI is realized. A 64 - synapse, 8 - neuron proof - of - concept chip is described. The synapse, which occupies only 4900 µm2 in a 2 - µm technology, includes a hybrid of nonvolatile and dynamic weight storage that provides fast and accurate learning as well as reliable long - term storage with no refreshing. The architecture is user - configurable in any one - hidden - layer topology. The user - interface is fully microprocessor compatible. Learning is accomplished with minimal external support; the user need only present inputs, targets, and a clock. Learning is fast and reliable. The chip solves four - bit parity in an average of 680 ms and is successful in about 96 % of the trials.

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