Underwater Acoustic Communication Channel Modeling using Deep Learning

Author:

Onasami Oluwaseyi1,Adesina Damilola1,Qian Lijun1

Affiliation:

1. Electrical and Computer Engineering, Prairie View A&M University, Texas A&M University System, USA

Funder

US DoD

Publisher

ACM

Reference28 articles.

1. Nesreen Ahmed , Amir Atiya , Neamat Gayar , and Hisham El-Shishiny . 2010. An Empirical Comparison of Machine Learning Models for Time Series Forecasting. Econometric Reviews 29 (08 2010 ), 594–621. https://doi.org/10.1080/07474938.2010.481556 10.1080/07474938.2010.481556 Nesreen Ahmed, Amir Atiya, Neamat Gayar, and Hisham El-Shishiny. 2010. An Empirical Comparison of Machine Learning Models for Time Series Forecasting. Econometric Reviews 29 (08 2010), 594–621. https://doi.org/10.1080/07474938.2010.481556

2. Link Adaptation on an Underwater Communications Network Using Machine Learning Algorithms: Boosted Regression Tree Approach

3. Lennert Appeltant , Miguel Soriano , Guy Van der Sande , Jan Danckaert, Serge Massar, J. Dambre, Benjamin Schrauwen, Claudio Mirasso, and Ingo Fischer. 2011 . Information processing using a single dynamical node as complex system. Nature communications 2 (09 2011), 468. https://doi.org/10.1038/ncomms1476 10.1038/ncomms1476 Lennert Appeltant, Miguel Soriano, Guy Van der Sande, Jan Danckaert, Serge Massar, J. Dambre, Benjamin Schrauwen, Claudio Mirasso, and Ingo Fischer. 2011. Information processing using a single dynamical node as complex system. Nature communications 2 (09 2011), 468. https://doi.org/10.1038/ncomms1476

4. Learning Deep Architectures for AI

5. A high-frequency warm shallow water acoustic communications channel model and measurements

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