Postdoctoral Researcher in statistical signal processing.
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: Spectrum sensing is a fundamental aspect of cognitive radio technology, tasked with detecting spectrum holes and unknown signal sources to improve spectrum management and resource ...
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Master signal processing with Python tools
Signal processing in Python is more approachable than ever with libraries like NumPy and SciPy. These tools make it easy to filter noise, analyze frequencies, and transform raw signals into meaningful ...
Off-the-shelf cema-cel clears MRD at more than triple the rate of observation alone—and may propel a shift to frontline use of CAR T-cell therapy when relapse is hard to detect. For years, the promise ...
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