Search Results - (( using simulation case algorithm ) OR ( data normalization based algorithm ))
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1
Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…A novel work has been done in producing simulated data based on empirical models of the real waveforms. …”
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2
EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…A novel work has been done in producing simulated data based on empirical models of the real waveforms. …”
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3
Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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4
Neural network based model predictive control for a steel pickling process
Published 2009“…The proposed algorithm is tested for control of a steel pickling process in several cases in simulation such as for set point tracking, disturbance, model mismatch and presence of noise. …”
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5
Multi-source data fusion framework for remote triaging and prioritization in telemedicine
Published 2015“…As telemedicine consists of three tiers (Sensors/ sources, Base station and Server), the simulation of the proposed frameworks as fusion algorithm in the base station and as healthcare services algorithm in the server was demonstrated. …”
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6
Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases
Published 2021“…The performance of MLѡвсн and four more modified ML-tests, namely MLtests with banded Cholesky estimator MLвсн with Thresholding MLтн with Weiszfeld Algorithm MLѡ and with Weiszfeld’s Algorithm Estimator and Thresholding MLѡтн had been examined using Type I error and power of test values in a simulation study. …”
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7
Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…Preprocessing removes noise from text data, normalizes sentiment word lists and undertakes temporal transformation. …”
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8
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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9
Fault detection and diagnosis using correlation coefficients
Published 2005“…Data collected with a process sampling time, TMSPC, of 4.6 hours and following the normal distribution are used as Nominal Operation Condition (NOC) data. …”
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10
Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with three training algorithms, namely, Standard Error Back-Propagation, Levenberg Marquardt and Resilient Back-Propagation algorithms. …”
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11
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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12
Embedded wearable EEG seizure detection in ambulatory state
Published 2014“…The system distinguishes between 'Normal' and 'Seizure' state using on-the-fly calculated features representing the statistical measures for specifically filtered signals from the raw data. …”
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13
Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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14
Modelling of intelligent intrusion detection system: making a case for snort
Published 2018“…Preprocessing was done to classify the output data into normal and attack. Performance evaluation was done using confusion matrix on the data. …”
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Proceeding Paper -
15
End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels
Published 2021“…The channel estimation results indicate that the adopted DL architectures are more robust than conventional techniques when fewer training pilots are used for both fading channels. Although the conventional algorithm, MMSE, outperforms the pro�posed algorithms when the number of pilots increased but it is not applicable in real transmission as it is required prior knowledge about the channel statistic which is not the case with DL-based estimators which rely only on the pilots. …”
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16
Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State
Published 2014“…The system distinguishes between 'Normal' and 'Seizure' state using on-the-fly calculated features representing the statistical measures for specifically filtered signals from the raw data. …”
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Conference or Workshop Item -
17
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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18
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…Whereas, the hash value of RBF bases that is identical with the hash value of the training data is used to select the RBF bases that is near to the training data. …”
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19
Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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20
Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems
Published 2008“…New time-domain (TD) adaptive estimation methods based on recursive least squares (RLS) and normalized least-mean squares (NLMS) algorithms are proposed. …”
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Thesis