TY - JOUR
T1 - Reducing Quantization Errors for Inner-Product Operations in Embedded Digital Signal Processing Systems [Tips & Tricks]
AU - Wang, Zhuo
AU - Zhang, Jintao
AU - Verma, Naveen
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11
Y1 - 2016/11
N2 - Inner-product operations are used extensively in embedded digital signal processing (DSP) systems. Their applications range from signal processing (filtering/convolution) to inference (classification). In embedded systems, resources (energy, area, etc.) are typically highly constrained, making tradeoffs with computational precision a fundamental concern. Indeed, with increasing requirements on algorithmic performance, many systems are trending toward higher computational precision to ensure accuracy of results.
AB - Inner-product operations are used extensively in embedded digital signal processing (DSP) systems. Their applications range from signal processing (filtering/convolution) to inference (classification). In embedded systems, resources (energy, area, etc.) are typically highly constrained, making tradeoffs with computational precision a fundamental concern. Indeed, with increasing requirements on algorithmic performance, many systems are trending toward higher computational precision to ensure accuracy of results.
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U2 - 10.1109/MSP.2016.2585278
DO - 10.1109/MSP.2016.2585278
M3 - Article
AN - SCOPUS:85032751290
SN - 1053-5888
VL - 33
SP - 141
EP - 147
JO - IEEE Audio and Electroacoustics Newsletter
JF - IEEE Audio and Electroacoustics Newsletter
IS - 6
M1 - 7737100
ER -