Variability-aware gradual aging for generating reliability figures of a neural measurement system

Author

Hellwege, Nico ; Heidmann, Nils ; Peters-Drolshagen, D. ; Paul, Sudipta

Author_Institution

Inst. of Electrodynamics & Microelectron. (ITEM.me), Univ. of Bremen, Bremen, Germany

fYear

2013

fDate

20-22 June 2013

Firstpage

380

Lastpage

385

Abstract

Systems for intracortical recording of neural activities underly strict reliability requirements. The system should operate without any dysfunction for at least one decade. Despite process variability also NBTI and CHC will introduce performance shifts, which need to be evaluated by the system designer. In order to estimate the lifetime the system, reliability figures need to be calculated. By reconfiguring netlists it is possible to combine Monte Carlo analysis and aging simulation. This method is used to determine reliability figures for a low noise amplifier as used within a typical neural measurement system. Results show the effect of degradation for various component performances and their according reliability figures.

Keywords

Monte Carlo methods; ageing; low noise amplifiers; reliability; CHC; Monte Carlo analysis; NBTI; low noise amplifier; neural activities; neural measurement system; reliability; variability-aware gradual aging; Aging; Analytical models; Degradation; Integrated circuit modeling; Integrated circuit reliability; Monte Carlo methods; Aging; Degradation; HCI; Monte Carlo; NBTI; Neural Measurement System; Reliability; Variability;

fLanguage

English

Publisher

ieee

Conference_Titel

Mixed Design of Integrated Circuits and Systems (MIXDES), 2013 Proceedings of the 20th International Conference

Conference_Location

Gdynia

Print_ISBN

978-83-63578-00-8

Type

conf

Filename

6613378