Compact Low-Power Calibration Mini-DACs for Neural Arrays With Programmable Weights  

Oleh:

Linares-Barranco, B. ; Serrano-Gotarredona, T. ; Serrano-Gotarredona, R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 14 no. 5 (2003), page 1207-1216.
Topik: CALIBRATION; low - power; calibration; neural arrays; programmable weights

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.9 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper considers the viability of compact low - resolution low - power mini digital - to - analog converters (mini - DACs) for use in large arrays of neural type cells, where programmable weights are required. Transistors are biased in weak inversion in order to yield small currents and low power consumptions, a necessity when building large size arrays. One important drawback of weak inversion operation is poor matching between transistors. The resulting effective precision of a fabricated array of 50 DAC s turned out to be 47 % (1.1 bits), due to transistor mismatch. However, it is possible to combine them two by two in order to build calibrated DAC s, thus compensating for inter - DAC mismatch. It is shown experimentally that the precision can be improved easily by a factor of 10 (4.8 % or 4.4 bits), which makes these DAC s viable for low - resolution applications such as massive arrays of neural processing circuits. A design methodology is provided, and illustrated through examples, to obtain calibrated mini - DAC s of a given target precision. As an example application, we show simulation results of using this technique to calibrate an array of digitally controlled integrate - and - fire neurons.

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