A Hybrid Signal Denoising Approach using Wavelet Decomposition and Neural Network-based Thresholding
Abstract: Signal denoising is a most important and fundamental task in signal processing. This is crucial for improving the quality of noisy data in applications like communication systems, audio ...
Abstract: This paper proposes a sparse Deep Neural Network (DNN) inference accelerator architecture that can be used for a reconfigurable edge computing platform that improves computational efficiency ...
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