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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments
Published 2025“…The rise of artificial intelligence (AI) has introduced innovative strategies to address these limitations. This paper presents a novel deep learning (DL)-based technique that leverages attention mechanisms to improve speech intelligibility through noise suppression. …”
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A discrete-time learning control algorithm
Published 1994“…A discretized version of the D-type learning control algorithm is presented for a MIMO linear discrete-time system. …”
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Learning control algorithms for tracking "slowly" varying trajectories
Published 1997“…For applications where the desired outputs are assumed to change "slowly", we present a D-type, PD-type, and PID-type learning algorithms. …”
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CNN and HEVC Video Coding Features for Static Video Summarization
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Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise
Published 2005“…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
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Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…Such data can be parsed using ML and AI approaches in designed to check attacks on CPSs. We present the new framework for the detection of cyberattacks, which makes use of AI and ML. …”
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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A discrete-time learning control algorithm for a class of linear time-invariant systems
Published 1995“…A discretized version of the D-type learning control algorithm is presented for a MIMO linear discrete-time system. …”
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A discrete-time stochastic iterative learning control algorithm for a class of nonlinear systems
Published 2005“…This article presents a stochastic algorithm that computes the learning gain matrix of a “D-type iterative learning control (ILC) algorithm for a class of discrete-time varying nonlinear systems with linear input/output actions having relative degree one. …”
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Multiclass feature selection with metaheuristic optimization algorithms: a review
Published 2022“…Metaheuristic algorithms have also been presented in four primary behavior-based categories, i.e., evolutionary-based, swarm-intelligence-based, physics-based, and human-based, even though some literature works presented more categorization. …”
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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…It will be used to determine courses learning results based on the empirical knowledge presented. …”
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Android Malware Detection Using Machine Learning
Published 2024“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. This paper presents a machine learning approach for Android malware detection. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…To improve the effectiveness and efficiency of the UniBFS algorithm, Redundant Features Elimination algorithm (RFE) is presented in this paper. …”
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