DSP-DIGITAL SIGNAL PROCESSOR-2020



A digital signal processor is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. DSPs are fabricated on MOS integrated circuit chips

DSP -based RF waveform aggregation for next generation mobile fronthauling
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The exponential traffic increase demands faster, high capacity, and quality of service (QoS) guaranteed services. Cloud radio access network (C-RAN) has become an emerging enabling technology introduced into 5G networks, and proposed to support the upcoming

FAULT DIAGNOSIS OF WIND TURBINE GEARBOXES THROUGH ON-SITE MEASUREMENTS AND VIBRATIONAL SIGNAL PROCESSING
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Condition monitoring of wind turbine gearboxes has attracted an impressive amount of attention in the wind energy literature. This happens for practical issues, as gearbox damages account for at least the 20% of wind turbines operational unavailability, and for The injection-locking or synchronization of an oscillator by an external periodic signal hereafter referred to the injection signal whose frequency is in the proximity of the natural frequency, more specifically the frequency of the first harmonic, of the oscillator under

Statistical and Graph-Based Signal Processing : Fundamental Results and Application to Cardiac Electrophysiology
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The history of electrophysiology, the study of electrical properties of biological cells and tissues, is long and fascinating. More than 200 years ago, Galvani discovered that the function of the nervous system is intrinsically linked to electrical activity [68], pushing the

Machine Learning for Signal Processing in Communications
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Page 1. Department of Electrical Engineering, Electronic Systems Group Alexios Balatsoukas-Stimming Machine Learning for Signal Processing in Communications January 14 Page 2. Machine Learning Communications: An Unlikely Alliance Alternative

Rethinking sketching as sampling: A graph signal processing
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Sampling of signals belonging to a low-dimensional subspace has well-documented merits for dimen- sionality reduction, limited memory storage, and online processing of streaming network data. When the subspace is known, these signals can be modeled as bandlimited graph

ECG Signal Processing Using Power Spectrum and Wavelet Transform: A Mathematical and Computing Aproach.
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This paper presents the description of a formal mathematical and computing method of Discrete Wavelet Transform (DWT) combined with auto-correlation power spectrum. Detail segments (high-pass) of the first and second scale level of DWT ( lifting scheme ) are

Deep Reinforcement Learning and Image Processing for Adaptive Traffic Signal Control
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In this paper, a traffic control system is build which can easily keep traffic in control using image processing techniques and deep reinforcement learning is presented. In this method, a camera is used in each stage of the traffic light in order to capture the roads where traffic is