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Neural network based predistortion of radio frequency power amplifiers
Published 2021Get full text
doctoralThesis -
22
Model Based Adaptive Tracking Scheme For Unknown MIMO Bilinear Systems
Published 2020“…Bilinear systems are attractive candidates for many dynamical processes, since they allow a significantly larger class of behaviour than linear systems, yet retain a rich theory which is closely related to the familiar theory of linear systems. …”
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Low-Complexity Machine Learning-based Behavioral Modeling of Power Amplifiers
Published 2025Get full text
doctoralThesis -
24
U-model Based Adaptive Tracking Scheme for Unknown MIMO Bilinear Systems
Published 2006“…Bilinear systems are attractive candidates for many dynamical processes, since they allow a significantly larger class of behaviour than linear systems, yet retain a rich theory which is closely related to the familiar theory of linear systems. …”
Get full text
Get full text
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25
U-Model Based Adaptive Tracking Scheme For Unknown MIMO Bilinear Systems
Published 2020“…Bilinear systems are attractive candidates for many dynamical processes, since they allow a significantly larger class of behaviour than linear systems, yet retain a rich theory which is closely related to the familiar theory of linear systems. …”
Get full text
article -
26
U-Model Based Adaptive Tracking Scheme For Unknown MIMO Bilinear Systems
Published 2020“…Bilinear systems are attractive candidates for many dynamical processes, since they allow a significantly larger class of behaviour than linear systems, yet retain a rich theory which is closely related to the familiar theory of linear systems. …”
Get full text
article -
27
U-Model Based Adaptive Tracking Scheme For Unknown MIMO Bilinear Systems
Published 2020“…Bilinear systems are attractive candidates for many dynamical processes, since they allow a significantly larger class of behaviour than linear systems, yet retain a rich theory which is closely related to the familiar theory of linear systems. …”
Get full text
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28
AI-based remaining useful life prediction and modelling of seawater desalination membranes
Published 2024Get full text
doctoralThesis -
29
UAV-based relay system for IoT networks with strict reliability and latency requirements
Published 2021“…The problem is formulated as a mixed-integer nonlinear program and linearization is proposed. A clustering-based approach providing low-complexity sub-optimal solutions is presented. …”
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Get full text
Get full text
Get full text
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Novel platinum(II)-based anticancer complexes and molecular hosts as their drug delivery vehicles
Published 2007“…These include linear or hairpin polyamide ligands that can recognise DNA sequences up to seven base-pairs in length and contain single platinum centres capable of forming monofunctional adducts with DNA. …”
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Get full text
Get full text
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Adherence and retention to the self-managed community-based Step Into Health program in Qatar (2012–2019)
Published 2022“…There were no significant main eects for sex or BMI on ADH, and no interaction eects (<i>p</i> ≥ 0.21) observed. …”
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34
Queuing-Based Optimization of EV Charging Stations: A Case Study of Manama City, Bahrain
Published 2025Get full text
doctoralThesis -
35
Deep transfer learning strategy in intelligent fault diagnosis of gas turbines based on the Koopman operator
Published 2024“…A <u>deep neural network</u>-based transfer learning framework is proposed for realizing a precise adaptive linear model called the deep transfer linear (DTL) model enabling reliable prediction of the system’s behavior in various situations and designing structured fault residuals. …”
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Machine Learning Based Photovoltaics (PV) Power Prediction Using Different Environmental Parameters of Qatar
Published 2019“…The ANN model outperforms other regression models, such as a linear regression model, M5P decision tree and gaussian process regression (GPR) model. …”
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Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection
Published 2025“…Current strategies for distraction detection widely rely on machine learning models, but the non-linear relationships among various data modalities complicate the identification of optimal combinations. …”