TY - GEN
T1 - Random Coding Error Exponent for the Bee-Identification Problem
AU - Tandon, Anshoo
AU - Tan, Vincent Y.F.
AU - Varshney, Lav R.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Consider the problem of identifying a massive number of bees, uniquely labeled with barcodes, using noisy measurements. We introduce this 'bee-identification problem characterize the random coding exponent, and derive efficiently computable bounds for this exponent. We demonstrate that joint decoding of barcodes has much better exponent than separate decoding followed by permutation inference.
AB - Consider the problem of identifying a massive number of bees, uniquely labeled with barcodes, using noisy measurements. We introduce this 'bee-identification problem characterize the random coding exponent, and derive efficiently computable bounds for this exponent. We demonstrate that joint decoding of barcodes has much better exponent than separate decoding followed by permutation inference.
UR - https://www.scopus.com/pages/publications/85081109162
U2 - 10.1109/ITW44776.2019.8989304
DO - 10.1109/ITW44776.2019.8989304
M3 - Conference contribution
AN - SCOPUS:85081109162
T3 - 2019 IEEE Information Theory Workshop, ITW 2019
BT - 2019 IEEE Information Theory Workshop, ITW 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Information Theory Workshop, ITW 2019
Y2 - 25 August 2019 through 28 August 2019
ER -