@inproceedings{0302b6e13cfe478986091be07b2b40bf,
title = "Fused floating point arithmetic for discrete wavelet transform",
abstract = "Floating point arithmetic provides high resolution and wide range for representing numbers. However it requires huge resources and high power consumption which makes it unfavorable for implementation in power constrained wearable devices. In this paper we present fused floating point arithmetic for realizing Discrete Wavelet Transform (DWT). Comparative analysis is performed to determine the advantages of fused floating point. Implementing DWT using fused floating point dot product required 22% less area than using conventional floating point arithmetic. Moreover the required power consumption is 67% less. DWT is chosen in the analysis since it is widely used in wearable ECG processors due to its inherent behavior to suppress noise.",
keywords = "Discrete wavelet transform, Dot product, Floating point, Fused floating point",
author = "Temesghen Tekeste and Hani Saleh and Baker Mohammad and Mohammed Ismail",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 59th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2016 ; Conference date: 16-10-2016 Through 19-10-2016",
year = "2016",
month = jul,
day = "2",
doi = "10.1109/MWSCAS.2016.7870140",
language = "British English",
series = "Midwest Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE 59th International Midwest Symposium on Circuits and Systems, MWSCAS 2016",
address = "United States",
}