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Physical Sciences and Mathematics Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Common Spatial Pattern-Based Feature Extraction From The Best Time Segment Of Bci Data, Önder Aydemi̇r
Common Spatial Pattern-Based Feature Extraction From The Best Time Segment Of Bci Data, Önder Aydemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Feature extraction is one of the most crucial stages in the field of brain computer interface (BCI). Because of its ability to directly influence the performance of BCI systems, recent studies have generally investigated how to modify existing methods or develop novel techniques. One of the most successful and well-known methods in BCI applications is the common spatial pattern (CSP). In existing CSP-based methods, the spatial filters were extracted either by using the whole data trial or by dividing the trials into a number of overlapping/nonoverlapping time segments. In this paper, we developed a CSP-based moving window technique to obtain …
Investigation Of The Most Appropriate Mother Wavelet For Characterizing Imaginary Eeg Signals Used In Bci Systems, Önder Aydemi̇r, Temel Kayikçioğlu
Investigation Of The Most Appropriate Mother Wavelet For Characterizing Imaginary Eeg Signals Used In Bci Systems, Önder Aydemi̇r, Temel Kayikçioğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Feature extraction is a very challenging task, since choosing discriminative features directly affects the recognition rate of the brain--computer interface (BCI) system. The objective of this paper is to investigate the effect of mother wavelets (MWs) on classification results. To this end, features were extracted from 3 different datasets using 12 MWs, and then the signals were classified using 3 classification algorithms, including k-nearest neighbor, support vector machine, and linear discriminant analysis. The experiments proved that Daubechies and Shannon were the most suitable wavelet families for extracting more discriminative features from imaginary EEG/ECoG signals.
A Wavelet-Based Feature Set For Recognizing Pulse Repetition Interval Modulation Patterns, Kenan Gençol, Nuray At, Ali̇ Kara
A Wavelet-Based Feature Set For Recognizing Pulse Repetition Interval Modulation Patterns, Kenan Gençol, Nuray At, Ali̇ Kara
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
A Comprehensive Comparison Of Features And Embedding Methods For Face Recognition, Hasan Serhan Yavuz, Hakan Çevi̇kalp, Ri̇fat Edi̇zkan
A Comprehensive Comparison Of Features And Embedding Methods For Face Recognition, Hasan Serhan Yavuz, Hakan Çevi̇kalp, Ri̇fat Edi̇zkan
Turkish Journal of Electrical Engineering and Computer Sciences
Face recognition is an essential issue in modern-day applications since it can be used in many areas for several purposes. Many methods have been proposed for face recognition. It is a difficult task since variations in lighting, instantaneous mimic varieties, posing angles, and scaling differences can drastically change the appearance of the face. To suppress these complications, effective feature extraction and proper alignment of face images gain as much importance as the recognition method choice. In this paper, we provide an extensive comparison of the state-of-the-art face recognition methods with the most well-known techniques used in feature representation. In order …
Ship-Radiated Noise Feature Extraction Using Multiple Kernel Graph Embedding And Auditory Model, Xinzhou Xu, Xinwei Luo, Chen Wu, Li Zhao
Ship-Radiated Noise Feature Extraction Using Multiple Kernel Graph Embedding And Auditory Model, Xinzhou Xu, Xinwei Luo, Chen Wu, Li Zhao
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.