Real-time transient error and induced noise cancellation in linear analog filters using learning-assisted adaptive analog checksums
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EditorInstitute of Electrical and Electronics Engineers (IEEE)
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Analog circuits are sensitive to signal aggressions and power supply noise, crosstalk coupling and alpha particle strikes can cause significant degradation of circuit's SNR. This research proposes a novel approach to real-time transient error and induced noise cancellation in linear analog circuits using analog checksums. It is based on the use of state space representations of analog filters and is a significant advancement over prior research that addressed only hard parametric deviations. A key innovation is the use of less than minimum distance checksum codes for error detection and correction using real-time learning of the likely source of transient errors and noise within the analog circuit. By running a simple hardware-directed search algorithm, the circuit 'learns' how best to compensate for the injected signal disturbances with low overhead under the assumption that the source of the injected errors/noise and the error/noise statistics are stationary over time. Successful simulations and preliminary experimental results demonstrate almost complete compensation of injected noise, therefore validating the proposal.
CitacióÁlvaro Gómez-Pau; Banerjee, S.; Chatterjee, A. Real-time transient error and induced noise cancellation in linear analog filters using learning-assisted adaptive analog checksums. A: IEEE International On-Line Testing Symposium. "Proceedings of the 2014 IEEE 20th International On-Line Testing Symposium (IOLTS): 7-9 July 2014, Hotel Cap Roig, Platja d’Aro, Catalunya, Spain". Platja d'Aro: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 25-30.
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