On the likelihood-based approach to modulation classification

By Fahed Hameed, Octavia A. Dobre, Dimitrie C. Popescu. IEEE Transactions on Wireless Communications, 2009

413 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/84fcb4074785c61657cf801d88f91ed84f12e341

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Mengchu Zhou
2. Wei Su
3. Jefferson L. Xu

In Artificial Intelligence

1. Mengchu Zhou
2. Wei Su
3. Jefferson L. Xu

In Molecular Biology

1. Mengchu Zhou
2. Wei Su
3. Jefferson L. Xu

Citations in the corpus

• Likelihood-Ratio Approaches to Automatic Modulation Classification (2011, methodology): “classifiers equipped with the MoM or LS estimator that is of the lower complexity than the ML type are termed as quasiHLRT (qHLRT) in [17] and [21].”