Electrical Engineering: المرسلات الحديثة
السجلات المعروضة 1341 -- 1360 من 2821
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End-to-end performance of transmission systems with relays over Rayleigh-fading channels
( IEEE , 2003 , Article)End-to-end performance of two-hops wireless communication systems with nonregenerative relays over flat Rayleigh-fading channels is presented. This is accomplished by deriving and applying some new closed-form expressions ... -
Optimal power allocation for relayed transmissions over Rayleigh-fading channels
( IEEE , 2004 , Article)Relayed transmission is a way to attain broader coverage by splitting the communication link from the source to the destination into several shorter links/hops. One of the main advantages of this communication technique ... -
A performance study of dual-hop transmissions with fixed gain relays
( IEEE , 2004 , Article)This letter presents a study on the end-to-end performance of dual-hop wireless communication systems equipped with nonregenerative fixed gain relays and operating over flat Rayleigh-fading channels. More specifically, it ... -
Average ber of multihop communication systems over fading channels
( IEEE , 2003 , Conference)Multihop transmission is a way to attain broader coverage by splitting the communication link from the source to the destination into several, possibly shorter links/hops. This paper presents an expression for the moment ... -
Performance of OFDM with M-QAM modulation and optimal loading over rayleigh fading channels
( IEEE , 2004 , Conference)We present optimum bit and power loading algorithms for orthogonal frequency division multiplexing (OFDM) systems using an M-ary quadrature amplitude modulation (M-QAM) scheme. Several scenarios for the amount of channel ... -
Performance enhancement of relay-assisted communications via binary feedback
( IEEE , 2004 , Conference)This paper proposes a modified two-hop wireless communication system and studies its performance. The modified system has a reliable feedback channel that carries a binary signal from the receiver to inform the transmitter ... -
Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs
( Elsevier Ltd , 2022 , Article)Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital ... -
Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-ray Images
( Springer , 2022 , Article)Novel coronavirus disease (COVID-19) is an extremely contagious and quickly spreading coronavirus infestation. Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which outbreak in 2002 ... -
COVID-19 infection localization and severity grading from chest X-ray images
( Elsevier Ltd , 2021 , Article)The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic ... -
Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network
( IEEE Computer Society , 2022 , Article)Objective: Noise and low quality of ECG signals acquired from Holter or wearable devices deteriorate the accuracy and robustness of R-peak detection algorithms. This paper presents a generic and robust system for R-peak ... -
A New Benchmark Problem for Structural Damage Detection: Bolt Loosening Tests on a Large-Scale Laboratory Structure
( Springer , 2022 , Conference)Monitoring the structural performance of engineering structures has always been pertinent for maintaining structural health and assessing the life cycle of structures. Structural Health Monitoring (SHM) and Structural ... -
3D Quantum Cuts for automatic segmentation of porous media in tomography images
( Elsevier Ltd , 2022 , Article)Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves ... -
An Overview of Deep Learning Methods Used in Vibration-Based Damage Detection in Civil Engineering
( Springer , 2022 , Conference)This paper presents a brief overview of vibration-based damage identification studies based on Deep Learning (DL) in civil engineering structures. The presence, type, size, and propagation of structural damage on civil ... -
A Social Distance Estimation and Crowd Monitoring System for Surveillance Cameras
( MDPI , 2022 , Article)Social distancing is crucial to restrain the spread of diseases such as COVID-19, but complete adherence to safety guidelines is not guaranteed. Monitoring social distancing through mass surveillance is paramount to develop ... -
One-Dimensional Convolutional Neural Networks for Real-Time Damage Detection of Rotating Machinery
( Springer , 2022 , Conference)This paper presents a novel real-time rotating machinery damage monitoring system. The system detects, quantifies, and localizes damage in ball bearings in a fast and accurate way using one-dimensional convolutional neural ... -
Structural Damage Detection in Civil Engineering with Machine Learning: Current State of the Art
( Springer , 2022 , Conference)This paper presents a brief overview of vibration-based structural damage detection studies that are based on machine learning (ML) in civil engineering structures. The review includes both parametric and nonparametric ... -
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ... -
Self-organized operational neural networks for severe image restoration problems
( Elsevier Ltd , 2021 , Article)Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image ... -
1D convolutional neural networks and applications: A survey
( Academic Press , 2021 , Article)During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with ... -
Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networks
( IEEE Computer Society , 2021 , Article)Despite the proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ...
