Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Emg Classification In Obstructive Sleep Apnea Syndrome And Periodic Limb Movement Syndrome Patients By Using Wavelet Packet Transform And Extreme Learning Machine, Necmetti̇n Sezgi̇n
Emg Classification In Obstructive Sleep Apnea Syndrome And Periodic Limb Movement Syndrome Patients By Using Wavelet Packet Transform And Extreme Learning Machine, Necmetti̇n Sezgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Electromyogram (EMG) signals, measured at the skin surface, provide crucial access to the muscle tones of a body. Some diseases, such as obstructive sleep apnea syndrome (OSAS) and periodic limb movement syndrome (PLMS), are closely associated with the electrical activity of muscle tones. In this paper, a hybrid model containing wavelet packet transform (WPT) plus an extreme learning machine (ELM) was proposed to classify EMG signals in OSAS and PLMS patients. At first, the WPT was used to extract the features of the EMG signal, and then these features were fed to the ELM classifier. The mean classification accuracy of …
Color Texture Image Classification Based On Fractal Features And Extreme Learning Machine, Erkan Tanyildizi
Color Texture Image Classification Based On Fractal Features And Extreme Learning Machine, Erkan Tanyildizi
Turkish Journal of Electrical Engineering and Computer Sciences
Texture classification, especially color texture classification, is considered a significant step in segmentation and object classification. The property of color and texture is important for characterizing objects in natural scenes. Fractal dimension (FD) has many applications in the field of image compression and image segmentation. A series of FD features, such as mean, standard deviation, lacunarity, kurtosis, skewness, entropy, inverse difference moment, contrast, energy, dissimilarity, homogeneity, and maximum probability, are investigated for obtaining the maximum discrimination. In this manuscript, a methodology is proposed that is based on FD and an extreme learning machine for color texture classification. Performance of the …