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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…The use of sensors known as Brain-Computer Interface (BCI) tool can monitor the physical processes and mental states that occur in the human brain. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. …”
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Electroencephalogram signal interpretation system for mobile robot
Published 2013“…In recent years, Brain-Computer Interface (BCI) research has provoked an enormous interest among researchers from different fields since it is an important element in assistive technology. …”
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Wavelet-based compression of medical images: Filter-bank selection and evaluation
Published 2003“…We evaluated the best types of filters suitable for medical images in providing low bit rate and low computational complexity. In this study a variety of wavelet filters are used to compress and decompress computed tomography (CT) brain and abdomen images. …”
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Evaluation of time-domain features for motor imagery movements using FCM and SVM
Published 2012“…In order to attain less computational complexity, five timedomain procedure, namely: Mean Absolute Value, Maximum peak value, Simple Square Integral, Willison Amplitude, and Waveform Length are used for feature extraction of EEG signals. …”
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Automated Region Growing for Segmentation of Brain Lesion in Diffusion-weighted MRI
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Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images
Published 2015“…In the proposed feature selection algorithm, the ordered nature of cognitive scores or ranks and the amount of error value that can be imposed by any feature over any rank are never considered. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…So far however, there has been little discussion about the effectiveness of the application of these models to computer and video games in particular. The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography
Published 2022“…The t-test analysis of the SSE between conventional-ground truth (median=5.45, SD=3.96) and automated-ground truth (median=0.73, SD=0.78) achieved p-value < 0.001 (p=5.10E-9). Conclusion: The automated AI-based algorithm significantly improved the ICH surface area measurement from the CT brain with higher accuracy and efficiency in comparison to the conventional method.…”
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Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram
Published 2018“…The interference of eye blink artifacts can cause serious distortion to electroencephalogram (EEG) which could bias the signal interpretation and reduce the classification accuracy in a brain-computer interface (BCI) application. To overcome this problem, an algorithm to automatically detect and remove the artifacts from EEG signals is highly desirable. …”
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Proceeding Paper -
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A Proposed Frame Work for Real Time Epileptic Seizure Prediction using Scalp EEG
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Evaluating the effectiveness of time-domain features for motor imagery movements using SVM
Published 2012“…In this work, in order to have less computational complexity, time-domain algorithms are employed to motor imagery signals. …”
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A Comparison of JPEG and Wavelet Compression Applied to CT Images
Published 2003“…This paper focuses on the quantitative comparison of lossy compression methods applied to a variety of 8-bit Computed Tomography (CT) images. Joint Photographic Experts Group UPEG) and Wavelet compression algorithms were used on a set of CT images, namely brain, chest, and abdomen. …”
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