Browsing School of Mechatronic Engineering (Articles) by Subject "Linear Discriminant Analysis (LDA)"

Now showing items 1-4 of 4

    • Classification of human emotion from eeg using discrete wavelet transform 

      Murugappan, M.; Ramachandran, Nagarajan; Sazali, Yaacob, Prof. Dr. (Scientific Research Publishing Inc, 2010-04)
      In this paper, we summarize the human emotion recognition using different set of electroencephalogram (EEG) channels using discrete wavelet transform. An audio-visual induction based protocol has been designed with more ...

    • Classification of speech dysfluencies using LPC based parameterization techniques 

      Hariharan, Muthusamy; Lim, Sin Chee; Ooi, Chia Ai; Sazali, Yaacob, Prof. Dr. (Springer Science+Business Media, LLC., 2011-01-20)
      The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients ...

    • Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors 

      Ammar, Zakaria; Ali Yeon, Md. Shakaff, Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Mohd Noor, Ahmad; Maz Jamilah, Masnan; Abdul Hallis, Abd Aziz; Nazifah, Ahmad Fikri; Abu Hassan, Abdullah; Latifah Munirah, Kamarudin (MDPI Publishing, 2010-09-28)
      An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and ...

    • Reckoning of facial grimacing scheme for patient agitation in critical care 

      Muhammad Naufal, Mansor; Sazali, Yaacob, Prof. Dr.; Nagarajan, Ramachandran, Prof. Dr. (Science Academy Publisher, 2011-03)
      Reckoning patient grimacing in Intensive Care Unit (ICU) is a crucial demand in checking routine procedure. Despite of detecting any physical change in the body of the patient, medical staff has to go up and down to the ...