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Ocean soundscape can be considered to be a sum of identifiable sources and unknown background sound called ambient noise. Ambient noise and its spatial, temporal and spectral variations have a significant impact on performance of sonar systems. These variations are severe in tropical shallow waters and lead to the complexities for prediction and modeling efforts. Underwater acoustic systems suffer...
Compressive imagers, e.g. the single-pixel camera (SPC), acquire measurements in the form of random projections of the scene instead of pixel intensities. Compressive Sensing (CS) theory allows accurate reconstruction of the image even from a small number of such projections. However, in practice, most reconstruction algorithms perform poorly at low measurement rates and are computationally very expensive...
Energy expenditure (EE) estimation from accelerometer-based wearable sensors is important to generate accurate assessment of physical activity (PA) in individuals. Approaches hitherto have mainly focused on using accelerometer data and features extracted from these data to learn a regression model to predict EE directly. In this paper, we propose a novel framework for EE estimation based on statistical...
Ambient noise has a profound impact on the performance of underwater systems, specifically in the tropical littoral waters. The site specific nature presents its unique challenge and efforts at mitigation have not been effective. Synthetic ambient noise generation has emerged as an effective Modeling and Simulation (M&S) tool for Signal to Noise Ratio (SNR) enhancement. Webster model of random...
Spatial-multiplexing cameras have emerged as a promising alternative to classical imaging devices, often enabling acquisition of ‘more for less’. One popular architecture for spatial multiplexing is the single-pixel camera (SPC), which acquires coded measurements of the scene with pseudo-random spatial masks. Significant theoretical developments over the past few years provide a means for reconstruction...
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