Browsing School of Mechatronic Engineering (Articles) by Author "Sazali, Yaacob, Prof. Dr."

Now showing items 1-20 of 47

    • Adaptive Neuro-Controller for three-axes attitude control of innovative satellite 

      Siti Maryam, Sharun; Mohd Yusoff, Mashor, Prof. Dr.; M. N. Norhayati; W. N. Hadani; Sazali, Yaacob, Prof. Dr. (Science Academy Publisher, 2011-03)
      There exists so many disturbance torques in space which may deviate the satellite from the desired attitude. To overcome the effects of the disturbance torques some stabilization has to be provided to the satellite. This ...

    • An adaptive predictive fuzzy logic for the altitude control of a micro-satellite 

      Ramachandran, Nagarajan; Pandiyan, Paulraj Murugesa, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Zuraidah, Md Zain, Prof. Dr.; Rusli, R. (Association pour la promotion des techniques de modelisation et de simulation dans l'entreprise Press, 2009)
      This paper deals with the attitude control of a micro-satellite in space using fuzzy logic principles. A micro-satellite in space can behave in an un-predictive way due the effect of variations in its system parameters and ...

    • Analysis of infant cry through weighted linear prediction cepstral coefficients and probabilistic neural network 

      Hariharan, Muthusamy; Lim, Sin Chee; Sazali, Yaacob, Prof. Dr. (Springer Science+Business Media, LLC., 2012)
      Acoustic analysis of infant cry signals has been proven to be an excellent tool in the area of automatic detection of pathological status of an infant. This paper investigates the application of parameter weighting for ...

    • Asynchronous brain machine interface-based control of a wheelchair 

      Hema, Chengalvarayan Radhakrishnamurthy; Murugesan Pandiyan, Paulraj, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Dr.; Ramachandran, Nagarajan, Prof. Dr. (Springerlink, 2011)
      A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is ...

    • Brain machine interface: Analysis of segmented EEG signal classification using short-time PCA and recurrent neural networks 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Madya (University of Basrah, 2008)
      Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients ...

    • Car cabin interior noise classification using temporal composite features and probabilistic neural network model 

      Paulraj, Murugesa Pandiyan, Prof. Dr.; Allan Melvin, Andrew; Sazali, Yaacob, Prof. Dr. (Trans Tech Publications Inc., 2014)
      Determination of vehicle comfort is important because continuous exposure to the noise and vibration leads to health problems for the driver and passengers. In this paper, a vehicle comfort level classification system has ...

    • 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 ...

    • Classification of speech dysfluencies with MFCC and LPCC features 

      Ooi, Chia Ai; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Lim, Sin Chee (Elsevier Ltd., 2012-02)
      The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech ...

    • Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals 

      Murugappan; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Biomedical Engineering Society of the R.O.C., 2011)
      In this paper, we present human emotion assessment using electroencephalogram (EEG) signals. The combination of surface Laplacian (SL) filtering, time-frequency analysis of wavelet transform (WT) and linear classifiers are ...

    • A comparative study of wavelet families for classification of wrist motions 

      Muthusamy, Hariharan; Chong, Yen Fook; Sindhu, Ravindran; Bukhari, Ilias; Sazali, Yaacob, Prof. Dr. (Elsevier Ltd., 2012-11)
      The selection of most suitable mother wavelet function is still an open research problem in various signal and image processing applications. This paper presents a comparative study of different wavelet families (Daubechies, ...

    • Comparison of classifying the material mechanical properties by using k-Nearest Neighbor and Neural Network Backpropagation 

      Intan Maisarah, Abd Rahim; Fauziah, Mat; Sazali, Yaacob, Prof. Dr. (Science Academy, 2011-03)
      This paper present a development of a system with non-destructive testing on the material to define the mechanical properties of material. The experimental and testing of the material mechanical properties using vibration ...

    • Comparison of speech parameterization techniques for the classification of speech disfluencies 

      Chong, Yen Fook; Hariharan, Muthusamy, Dr.; Lim, Sin Chee; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Scientific and Technical Research Council of Turkey, 2013-12)
      Stuttering assessment through the manual classification of speech disfluencies is subjective, inconsistent, time-consuming, and prone to error. The aim of this paper is to compare the effectiveness of the 3 speech feature ...

    • Detection of human stress using short-term ECG and HRV signals 

      Karthikeyan, Palanisamy; Murugappan, Muthusamy, Dr.; Sazali, Yaacob, Prof. Dr. (World Scientific Publishing Company, 2013-04)
      This paper introduces a method for resolving the problem of human stress detection through short-term (less than 5 min) electrocardiogram (ECG) and heart rate variability (HRV) signals. The explored methodology helps to ...

    • Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Sazali, Yaacob, Prof. Dr. (Inderscience Publisher, 2011)
      This paper proposes a feature extraction method based on time-domain energy variation for the detection of vocal fold pathology. In this work, two different vocal fold problems (vocal fold paralysis and edema) are taken ...

    • Diagnosis of voices disorders using MEL scaled WPT and functional link neural network 

      Paulraj, Muregesa Pandiyan, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy (Biomedical Fuzzy Systems Association (BMFSA), 2008-03-31)
      Nowadays voice disorders are increasing dramatically due to the modern way of life. Most of the voice disorders cause changes in the voice signal. Acoustic analysis on the speech signal could be a useful tool for ...

    • EEG based detection of conductive and sensorineural hearing loss using artificial neural networks 

      Pandiyan, Paulraj Murugesa , Prof. Dr.; Subramaniam, Kamalraj; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr.; Hema, C. R. (Advanced Institute of Convergence IT, 2013-05)
      In this paper, a simple method has been proposed to distinguish the normal and abnormal hearing subjects (conductive or sensorineural hearing loss) using acoustically stimulated EEG signals. Auditory Evoked Potential (AEP) ...

    • Electrocardiogram-based emotion recognition system using empirical mode decomposition and discrete fourier transform 

      Jerritta, S.; Murugappan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (John Wiley & Sons, Inc., 2014)
      Emotion recognition using physiological signals has gained momentum in the field of human computer–interaction. This work focuses on developing a user-independent emotion recognition system that would classify five emotions ...

    • Emotion recognition from facial EMG signals using higher order statistics and principal component analysis 

      Selvaraj, Jerritta; Murugappan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Taylor & Francis, 2014-04)
      Higher order statistics (HOS) is an efficient feature extraction method used in diverse applications such as bio signal processing, seismic data processing, image processing, sonar, and radar. In this work, we have ...

    • Face recognition using eigenfaces and neural networks 

      Mohamed Rizon; Muhammad Firdaus, Hashim; Puteh, Saad; Sazali, Yaacob, Prof. Dr.; Mohd Rozailan, Mamat; Ali Yeon, Md Shakaff, Prof. Dr.; Abdul Rahman, Saad; Hazri, Desa, Dr.; Karthigayan, M. (Science Publications, 2006)
      In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is ...