References
Liu B, Wang Z, Zhu W T, et al. An ultra-low power always-on keyword spotting accelerator using quantized convolutional neural network and voltage-domain analog switching network-based approximate computing. IEEE Access, 2019, 7: 186456–186469
Zhang Q R, Xie Q S, Duan K F, et al. A digital signal processor (DSP)-based system for embedded continuous-time cuffless blood pressure monitoring using single-channel PPG signal. Sci China Inf Sci, 2020, 63: 149402
Waris H, Wang C H, Liu W Q. Hybrid low radix encoding-based approximate booth multipliers. IEEE Trans Circ Syst II, 2020, 67: 3367–3371
Boro B, Reddy K M, Kumar Y B N, et al. Approximate radix-8 Booth multiplier for low power and high speed applications. Microelectron J, 2020, 101: 104816
Farshchi F, Abrishami M S, Fakhraie S M. New approximate multiplier for low power digital signal processing. In: Proceedings of the 17th CSI International Symposium on Computer Architecture & Digital Systems, 2013
Jiang H L, Santiago F J H, Mo H, et al. Approximate arithmetic circuits: a survey, characterization, and recent applications. Proc IEEE, 2020, 108: 2108–2135
Varga A, Steeneken H J M. Assessment for automatic speech recognition: II. NOISEX-92: a database and an experiment to study the effect of additive noise on speech recognition systems. Speech Commun, 1993, 12: 247–251
Acknowledgements
This work was supported by the National Science and Technology Major Project (Grant No. 2018ZX01031101-005) and National Natural Science Foundation of China (Grant No. 61904028).
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Liu B, Zhang Z L, and Cai H have the same contribution to this work.
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Liu, B., Zhang, Z., Cai, H. et al. Self-compensation tensor multiplication unit for adaptive approximate computing in low-power CNN processing. Sci. China Inf. Sci. 65, 149403 (2022). https://doi.org/10.1007/s11432-021-3242-6
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DOI: https://doi.org/10.1007/s11432-021-3242-6