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Augmented real-valued time-delay neural network for compensation of distortions and impairments in wireless transmitters
A digital predistorter, modeled by an augmented real-valued time-delay neural network
(ARVTDNN), has been proposed and found suitable to mitigate the nonlinear distortions of …
(ARVTDNN), has been proposed and found suitable to mitigate the nonlinear distortions of …
Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey
The primary objective of this study was to apply the ANN (artificial neural network) model
with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production …
with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production …
High precision eye tracking based on electrooculography (EOG) signal using artificial neural network (ANN) for smart technology application
Electrooculography (EOG) signal is the potential difference between the cornea and the
retina of the eye. The voltage amplitude changes when the eye moves in various directions …
retina of the eye. The voltage amplitude changes when the eye moves in various directions …
Common and special knowledge-driven TSK fuzzy system and its modeling and application for epileptic EEG signals recognition
Takagi-Sugeno-Kang (TSK) fuzzy systems are well known for their good balances between
approximation accuracy and interpretability. Among a wide variety of existing TSK fuzzy …
approximation accuracy and interpretability. Among a wide variety of existing TSK fuzzy …
Grey prediction with residual modification using functional-link net and its application to energy demand forecasting
Purpose Energy demand is an important economic index, and demand forecasting has a
significant role when devising energy development plans for cities or countries. GM (1, 1) …
significant role when devising energy development plans for cities or countries. GM (1, 1) …
Energy management in wireless sensor networks based on naïve bayes, MLP, and SVM classifications: A comparative study
Maximizing wireless sensor networks (WSNs) lifetime is a primary objective in the design of
these networks. Intelligent energy management models can assist designers to achieve this …
these networks. Intelligent energy management models can assist designers to achieve this …
[HTML][HTML] Migration and mutation (MeTa) hybrid trained ANN for dynamic spectrum access in wireless body area network
Conventional radio transmission for wireless patient monitoring systems (WPMS)
experiences spectrum overcrowding and congestion. To address this issue, dynamic …
experiences spectrum overcrowding and congestion. To address this issue, dynamic …
Prediction of suspended sediment loading by means of hybrid artificial intelligence approaches
The main aim of the research is to use the artificial neural network (ANN) model with the
artificial bee colony (ABC) and teaching–learning-based optimization (TLBO) algorithms for …
artificial bee colony (ABC) and teaching–learning-based optimization (TLBO) algorithms for …
Design of multiple share creation with optimal signcryption based secure biometric authentication system for cloud environment
Biometric authentication plays a vital role in the cloud computing (CC) environment to
accomplish security and privacy. Several kinds of biometrics are used for the authentication …
accomplish security and privacy. Several kinds of biometrics are used for the authentication …
Optimizing functional link neural network learning using modified bee colony on multi-class classifications
Abstract Functional Link Neural Network (FLNN) has emerged as an important tool for
solving classification problems and widely applied in many engineering and scientific …
solving classification problems and widely applied in many engineering and scientific …