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Creators/Authors contains: "Anjum, Khizar"

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  1. ; (, IEEE Journal on Selected Areas in Communications)
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  2. ; ; ; ; (, IEEE)
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  3. ; ; (, IEEE Journal of Biomedical and Health Informatics)
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  4. ; ; (, International Conference on Underwater Networks & Systems (WUWNet))
    Traditional methods for coding underwater acoustic communications are bound to be surpassed by methods optimizing for source-channel coding jointly. However, the complexity of joint-optimization has thwarted successful breakthroughs in this area. We, therefore, present a novel approach, where we model the coding problem as the translation problem of the input sequence to another ‘language’, depending on the estimated channel conditions. We use Long Short-Term Memory (LSTM)-based sequence-to-sequence models to enable this and explain our approach in detail. 
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