TY - GEN
T1 - Error Correction Coding of Stochastic Numbers Using BER Measurement
AU - Ishikawa, Ryota
AU - Tawada, Masashi
AU - Yanagisawa, Masao
AU - Togawa, Nozomu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - In electric circuits, errors are ineluctable. When upper bits of binary signals flip due to noise, the value will increase or decrease drastically. On the other hand, if stochastic numbers are used, the change on their values are the same since all the bits have the same weight. Therefore, stochastic computing, a computation method based on stochastic numbers, is attracting interest. Stochastic computing does have error tolerance, but cannot restore the bit stream if the bits are erroneous. Here, this paper focuses on evaluating the error-free value from the bit error rate and the erroneous value. In this paper, we propose a method to correct errors of stochastic numbers by measuring the bit error rate and filtering the values properly. From experimental evaluations, in environment with errors of more than 21%, this proposal will give a better peak-signal-to-noise ratio compared with a conventional error correction coding.
AB - In electric circuits, errors are ineluctable. When upper bits of binary signals flip due to noise, the value will increase or decrease drastically. On the other hand, if stochastic numbers are used, the change on their values are the same since all the bits have the same weight. Therefore, stochastic computing, a computation method based on stochastic numbers, is attracting interest. Stochastic computing does have error tolerance, but cannot restore the bit stream if the bits are erroneous. Here, this paper focuses on evaluating the error-free value from the bit error rate and the erroneous value. In this paper, we propose a method to correct errors of stochastic numbers by measuring the bit error rate and filtering the values properly. From experimental evaluations, in environment with errors of more than 21%, this proposal will give a better peak-signal-to-noise ratio compared with a conventional error correction coding.
KW - error correction
KW - error probability
KW - stochastic computing
KW - stochastic number
UR - http://www.scopus.com/inward/record.url?scp=85073749755&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073749755&partnerID=8YFLogxK
U2 - 10.1109/IOLTS.2019.8854450
DO - 10.1109/IOLTS.2019.8854450
M3 - Conference contribution
AN - SCOPUS:85073749755
T3 - 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design, IOLTS 2019
SP - 243
EP - 246
BT - 2019 IEEE 25th International Symposium on On-Line Testing and Robust System Design, IOLTS 2019
A2 - Gizopoulos, Dimitris
A2 - Alexandrescu, Dan
A2 - Papavramidou, Panagiota
A2 - Maniatakos, Michail
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2019
Y2 - 1 July 2019 through 3 July 2019
ER -