Scholars@Duke

Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data.

Publication ,  Conference
Banerjee, T; Whipps, GT; Gurram, P; Tarokh, V
Published in: GlobalSIP
2018
Publisher Link

Duke Scholars

Vahid Tarokh
Author Vahid Tarokh Electrical and Computer Engineering

Published In

GlobalSIP

ISBN

978-1-7281-1295-4

Publication Date

2018

Start / End Page

126 / 130

Publisher

IEEE
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Banerjee, T., Whipps, G. T., Gurram, P., & Tarokh, V. (2018). Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data. In GlobalSIP (pp. 126–130). IEEE.
Banerjee, Taposh, Gene T. Whipps, Prudhvi Gurram, and Vahid Tarokh. “Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data.” In GlobalSIP, 126–30. IEEE, 2018.
Banerjee T, Whipps GT, Gurram P, Tarokh V. Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data. In: GlobalSIP. IEEE; 2018. p. 126–30.
Banerjee, Taposh, et al. “Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data.” GlobalSIP, IEEE, 2018, pp. 126–30.
Banerjee T, Whipps GT, Gurram P, Tarokh V. Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data. GlobalSIP. IEEE; 2018. p. 126–130.

Published In

GlobalSIP

ISBN

978-1-7281-1295-4

Publication Date

2018

Start / End Page

126 / 130

Publisher

IEEE