Search Results - (( motion estimation means algorithm ) OR ( whale optimisation system algorithm ))
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Having those said, this study proposes BESS optimisation to reduce the total system losses using modified Whale Optimisation Algorithm (WOA) with high exploration and exploitation features. …”
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Investigating dam reservoir operation optimization using metaheuristic algorithms
Published 2023“…Dams; Digital storage; Heuristic algorithms; Optimal systems; Reservoir management; Reservoirs (water); Time series analysis; Dam reservoir operation optimization; Dam reservoirs; Harris hawk optimization; Levy flights; Levy-flight whale optimization algorithm; Metaheuristic; Optimisations; Optimization algorithms; Reservoir operation optimizations; Whale optimization algorithm; Optimization; algorithm; dam; hydroelectric power; optimization; power generation; reservoir; water storage; Iran…”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…Moreover, we investigate the behavior of our algorithm under challenging conditions including the subject's motions and illumination variation, which shows that our algorithm can reduce the influences of illumination interference and rigid motions significantly. …”
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A new Doppler Spread Estimation Algorithm Based on Zero Crossings of The Auto-correlation
Published 2010“…A comparison between our proposed algorithm and the algorithm proposed by Tevfik Yucek in term of the Normalized Mean Square Error has been shown.…”
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Data filtering of 5-axis inertial measurement unit using kalman filter
Published 2013“…The main contribution of these algorithms is the in-motion alignment approach with unknown initial conditions. …”
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Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility
Published 2018“…The results of simulation reveal that the proposed estimators are efficient based on the bias, variance, and mean square error. …”
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Parameter estimation of stochastic differential equation
Published 2012“…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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Detection and Classification of Moving Objects for an Automated Surveillance System
Published 2006“…Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Detection and classification of moving objects for an automated surveillance system
Published 2006“…Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Detection and classification of moving objects for an automated surveillance system
Published 2006“…Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon
Published 2020“…With regards to the AAMI standard, the mean ± SD of difference between the estimated and the gold standard SBP improved from 4.5±28.6 mmHg to -0.3±5.8mmHg and -0.6±5.4 mmHg using the MLR and SVR, respectively. …”
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An active lower-extremity exoskeleton for synchronous mobility assistance in lifting and carrying manual handling task / Sado Fatai
Published 2019“…The control system can assist wearers’ movement by a new synergy of three controller algorithms: a dual unscented Kalman filter (DUKF) for trajectory estimation and model update, an impedance controller for generation of assistive torque, and a new supervisory control algorithm for pilot movement detection and synchronization with the exoskeleton. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…To improve the proposed algorithm, GA was utilized to identify the best choice for ‘‘mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function. …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Although motor imagery signals have been used in assisting the hand grasping motion amongst others motions, nonetheless, such signals are often difficult to be generated. …”
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CNN-SVO: improving the mapping in semi-direct visual odometry using single-image depth prediction
Published 2019“…Reliable feature correspondence between frames is a critical step in visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) algorithms. In comparison with existing VO and V-SLAM algorithms, semi-direct visual odometry (SVO) has two main advantages that lead to state-of-the-art frame rate camera motion estimation: direct pixel correspondence and efficient implementation of probabilistic mapping method. …”
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Conference or Workshop Item -
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…A parametric model based on Hill Muscle Model (HMM) to estimate the knee joint moment is developed for both experiments protocols. …”
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