基于实时学习误差补偿的低成本容错模拟电路设计

Suvadeep Banerjee, Álvaro Gómez-Pau, A. Chatterjee
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引用次数: 5

摘要

过去已经提出了基于模拟校验和的线性电路容错,但由于误差补偿的高成本和复杂性,而其他基于冗余的方法具有令人难以接受的开销,因此仍然是一个理论工件。为了解决这一问题,本研究为广泛应用的线性模拟电路开发了新的低成本误差补偿方法。基于尝试和错误的补偿学习方法结合使用小于最小距离码用于容错。与之前的纠错方案相比,这大大节省了硬件,并且纠错延迟的增加最小。它显示了模拟电路中的双重故障是如何使用现有技术无法实现的,可以使用提出的故障学习方法进行补偿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of low cost fault tolerant analog circuits using real-time learned error compensation
Analog checksum based fault tolerance for linear circuits has been proposed in the past but remains a theoretical artifact due to the high cost and complexity of error compensation while other redundancy based methods have prohibitive overheads. To resolve this, new low cost error compensation methods for widely used linear analog circuits are developed in this research. Trial and error based compensation learning methods combined with the use of less than minimum distance codes are used for failure tolerance. This results in significant hardware savings over prior correction schemes with minimal increase in error correction latency. It is shown how dual failures in analog circuits, not possible with existing techniques, can be compensated using the proposed fault-learning approach.
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