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Titlebook: Signal Processing and Analysis Techniques for Nuclear Quadrupole Resonance Spectroscopy; Cristian Monea,Nicu Bizon Book 2022 The Editor(s)

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Signal Processing and Analysis Techniques for Nuclear Quadrupole Resonance Spectroscopy978-3-030-87861-0Series ISSN 1860-4862 Series E-ISSN 1860-4870
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Methods and Equipment for Signal Acquisition and Analysis for the Detection of Prohibited Substancemethods and equipment developed for scanning luggage or persons. This chapter aims to be a bibliographic study of methods and equipment for the acquisition and analysis of signals for the detection of prohibited substances, starting from the general framework of detection theory and summarizing the main detection techniques.
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Implementation of a Signal Pre-processing, Processing and Analysis System for Nuclear Quadrupole Re solutions are proposed for the factors that affect the performance of detection, and the hardware and software components of the system are detailed. Finally, the evaluation results of the developed system are presented.
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Book 2022signal detection is introduced using artificial intelligence/deep learning techniques. The book will be useful for for researchers and practitioners in the areas of electrical engineering, signal processing and analysis, applied spectroscopy, as well as for security or laboratory equipment manufacturers..
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Methods and Equipment for Signal Acquisition and Analysis for the Detection of Prohibited Substancemethods and equipment developed for scanning luggage or persons. This chapter aims to be a bibliographic study of methods and equipment for the acquisition and analysis of signals for the detection of prohibited substances, starting from the general framework of detection theory and summarizing the
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Solutions to Improve NQR Detection, the generalization of the algorithm using transfer learning is studied, so that it has performances at least as good as those presented so far, on spectrometers with different transfer characteristics, which can influence the response signal. Then the application of autoencoders to reduce the noise
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