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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
element » elements (Expand Search)
relating » regulating (Expand Search), relations (Expand Search), relative (Expand Search)
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A forward-backward Kalman for the estimation of time-variant channels in OFDM
Published 2005“…In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem-a structure induced by the data and channel constraints. …”
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84
An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
Published 0000“…In this paper, we propose an expectation-maximization algorithm for joint channel and data recovery in fast fading environments. …”
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85
An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …”
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86
Brain Source Localization in the Presence of Leadfield Perturbations
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87
Shuffled Linear Regression with Erroneous Observations
Published 2019“…Existing methods are either applicable only to data with limited observation errors, work only for partially shuffled data, sensitive to initialization, and/or work only with small dimensions. …”
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High-order parametrization of the hypergeometric-Meijer approximants
Published 2023“…We also show that such extension of the hypergeometric resummation algorithm is able to employ non-perturbative information like strong-coupling and large-order asymptotic data which are always used to accelerate the convergence. …”
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A survey and comparison of wormhole routing techniques in a meshnetworks
Published 1997“…These multiprocessing systems consist of processing elements or nodes which are connected together by interconnection networks in various topologies. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
Published 2023“…A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. …”
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On sensor selection in mobile devices based on energy, application accuracy, and context metrics
Published 2013“…Continuously collecting sensor data on mobile devices helps in capturing important contextual information related to the user location, activity, and surrounding environment. …”
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94
Benchmark on a large cohort for sleep-wake classification with machine learning techniques
Published 2019“…In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …”
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Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE
Published 2022“…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …”
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96
Cross entropy error function in neural networks
Published 2002“…The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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97
Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
Published 2022“…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”
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A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. …”
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An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation
Published 2019“…However, the current solutions proposed for the use of crowdsensing for the collection of traffic related data adopt an opportunistic continuous sensing approach, which entails high resource consumption on the server and mobile device side, a high communication overhead, while offering little control of the users over the sensing activity. …”
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Plant disease detection using drones in precision agriculture
Published 2023“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”