Paulraj Murugesa Pandiyan, Assoc. Prof. Dr.: Recent submissions

Now showing items 21-40 of 113

    • Improving classification of EEG signals for a four-state brain machine interface 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012)
      Neural network classifiers are one among the popular modes in the design of classifiers for electroencephalograph based brain machine interfaces. This study presents algorithms to improve the classification performance of ...

    • Application-specific multichannel EEG data acquisition system for portable biomedical application 

      Paulraj, Murugesa Pandian, Dr.; Abdul Hamid, Adom, Prof. Dr.; Tung, Kai Xu; Subramaniam, Kamalraj (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      This paper presents the design and construction of a low power application-specific EEG bio-potential multichannel amplifier with high common mode rejection ratio (CMRR) and high input impedance. The bio-potential amplifier ...

    • Moving vehicle recognition and classification based on time domain approach 

      Paulraj, Murugesa Pandian, Dr.; Abdul Hamid, Adom, Prof., Dr.; Sundararaj, Sathishkumar; Norasmadi, Abdul Rahim (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      Differentially Hearing Ability Enabled (DHAE) community cannot discriminate the sound information from a moving vehicle approaching from their behind. This research work is mainly focused on recognition of different vehicles ...

    • Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks 

      Paulraj, Murugesa Pandiyan, Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shukry, Abdul Majid; Mohd Nor Fakhzan, Mohd Kazim; Pranesh, Krishnan (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      This paper discusses about the detection of damages present in the steel plates using nondestructive vibration testing. A simple experimental model has been developed to hold the steel plate complying with the simply ...

    • Measuring the speech intelligibility of the sound reinforced classroom 

      M. Ridhwan, Tamjis; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Ahmad Nazri, Abdullah (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      Classroom speech intelligibility has become one of the main concerns in schools and other learning institutions development nowadays. This is because the qualities of student’s perceptions towards teacher are essentials ...

    • A simple sign language recognition system using affine moment blur invariant features 

      Rajkumar, Palaniappan; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shuhanaz, Zanar Azalan (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      Sign language recognition is one of the most promising sub-fields in gesture recognition research. Effective sign language recognition would grant the deaf and hard-of-hearing expanded tools for communicating with both ...

    • Vehicle interior sound quality evaluation using energy based features 

      Allan, Melvin Andrew; Paulraj, Murugesa Pandian, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      The comfort in the car interior is already become a need for the passengers and the buyers. Due to high competition in car industries, all the car manufacturers are concentrating in improving the interior noise comfort of ...

    • BMI using spectral energy entropy for colour visual tasks 

      Divakar, Purushothaman; Paulraj, Murugesa Pandiyan, Prof. Madya Dr.; Abdul Hamid, Adom, Dr.; Hema, Chengalvarayan Radhakrishnamurthy (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      EEG signals are the electrophysiological measures of brain function and it is used to develop a Brain machine Interface. A Brain machine Interface (BMI) system is used to provide a communication and control technology ...

    • The use of openCV in Traffic Surveillance System (TSS) 

      Zainab Nazar, Khalil Wafi; R. Badlishah, Ahmad, Dr.; Paulraj, Murugrsa Pandiyan, Prof. Madya Dr. (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      Due to the increase of traffic accidents over the last few years; the development of surveillance systems has increasing attention. The use of the video cameras is one solution to solve the traffic problems, Smart cameras ...

    • Synchronous brain machine interface design using focused time delay networks 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Ramachandran, Nagarajan, Prof. Dr. (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Focused time delay neural network based design for a four-state Brain Machine Interface (BMI) to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively using two bipolar electrodes are used in the ...

    • Classification of EEG colour imagination tasks based BMI using energy and entropy features 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Hema, Chengalvarayan Radhakrishnamurthy; Purushothaman, Divakar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Electroencephalogram (EEG) signals are the electrophysiological measures of brain function and it is used to develop a brain machine interface. Brain machine interface (BMI) system is used to provide a communication and ...

    • Moving vehicle identification using artificial neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Siti Marhainis, Othman; Sundararaj, Sathish Kumar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Hearing impaired people cannot distinguish the sound from a moving vehicle approaching from their behind. They often face a risky situation while they are in outdoors. In this paper, a simple algorithm is proposed to ...

    • Image quality assessment using Elman neural network model 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Palaniappan, Rajkumar; Mohd Shuhanaz, Zanar Azalan (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment algorithms is to automatically assess the quality of images or videos ...

    • Classification of vehicle noise comfort level using feedforward neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Siti Marhainis; Andrew, Allan Melvin (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)

    • A phoneme based sign language recognition system using interleaving feature and neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shuhanaz, Zanar Azalan; Palaniappan, Rajkumar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      A sign language is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns. Sign languages are commonly developed in hearing impaired communities, which can include ...

    • Discrimination of pathological voices using systole activated neural network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy, Dr. (Noise, Vibration and Comfort Research Group, 2007-11-27)
      The discrimination of normal and pathological voices using noninvasive acoustical analysis features helps speech specialits to perform accurate diagnoses of vocal and voices disease. Acoustic analysis is a non-invasive ...

    • Improved back propagation neural network for the diagnosis of pathological voices 

      Paulraj, M.P.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Hariharan, Muthusamy (Association for Advancedment of Modelling and Simulation Techniques in Entreprises (A.M.S.E), 2008)
      Most of vocal and voice diseases cause changes in the voice. ENT clinicians use acoustic voice analysis to characterize the pathological voices. Nowadays, voice diseases are increasing dramatically due to unhealthy social ...

    • Identification of vocal and voice disorders 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Rizon, Mohammed Juhari, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2007-10-25)
      The discrimination of normal and pathological voices using noninvasive acoustic analysis helps to perform accurate identification of voice disorders and diagnoses of vocal and voice disease. Acoustic analysis is a non- ...

    • Neural network based detection of voice disorders using energy spectrum and equal-loudness contours 

      Murugesa Pandian, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Teknologi MARA (UiTM)Faculti of Electrical Engineering, 2008-03-07)
      Impairment of vocal function can have a major impact on the quality of life, severely limiting communication at work and affecting all social aspect of daily life. In the recent years, voice disease are increasing dramatically ...

    • Diagnosis of voice disorders using band energy spectrum in wavelet domain 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2008-03-08)
      In the evolution of quality of speech, acoustic analyses of normal and pathological voices have become increasingly interesting to researchers in laryngology and speech pathologies. Vocal signal information plays an important ...