Browsing Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. by Title

Now showing items 34-53 of 114

    • Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot 

      Mohd Saifizi, Saidon; Hazry, Desa; Paulraj, Murugesa; Mohd Sofian, M. Rosbi (Universiti Malaysia Perlis, 2009-10-11)
      Machine vision can be described as a useful robotic sensor since it mimics the human sense of vision and allows for non-contact measurement of the environment. The infinite number of possible poses relative to the viewer ...

    • Development of attitude control system on RCM3400 microcontroller 

      Yaakop, M.; Sazali, Yaacob, Prof. Dr.; Abdul Rahman, Mohd Saad, Prof Madya; Zain, M.; Paulraj, Murugesa Pandiyan, Prof. Dr.; Hariharan, M.; Nagarajan, R., Prof. Dr.; Kay, W. S.; Arshad, A. S. (Institute of Electrical and Electronic Engineers (IEEE), 2009-02-17)
      This paper describes the development of a nanosatellite altitude control system (ACS) which employ a filter base controller with comparison with a simple adaptive predictive fuzzy logic controller (APFLC) for a 1, 2 and 3 ...

    • Diagnosis of vocal fold pathology using time-domain features and systole activated neural network 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Hariharan, M. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)
      Due to the nature of job, unhealthy social habits and voice abuse, the people are subjected to the risk of voice problems. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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) ...

    • EEG classification using radial basis PSO neural network for brain machine interfaces 

      Paulraj, Murugesapandian; Hema, Chengalvarayan Radhakrishnamurthy; Ramachandran, Nagarajan; Sazali, Yaacob; Abdul Hamid, Adom (Institute of Electrical and Electronics Engineering (IEEE), 2007-12)
      Brain Machine Interfaces use the cognitive abilities of patients with neuromuscular disorders to restore communication and motor functions. At present, only EEG and related methods, which have relatively short time constants, ...

    • EEG signal classification using Particle Swarm Optimization (PSO) neural network for brain machine interfaces 

      Paulraj, Murugesapandian; Hema, Chengalvarayan Radhakrishnamurthy; Ramachandran, Nagarajan; Sazali, Yaacob; Abdul Hamid, Adom (Association for the Advancement of Modelling & Simulation Techniques in Enterprises (A.M.S.E.), 2008)
      The brain uses the neuromuscular channels to communicate and control its external environment, however many disorders can disrupt these channels. Amyotrophic lateral sclerosis is one such disorder which impairs the neural ...

    • Entropy based feature extraction for motorbike engine faults diagnosing using neural network and wavelet transform 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Zin, M.Z.M. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)
      The sound of working vehicle provides an important clue for engine faults diagnosis. Endless efforts have been put into the research of fault diagnosis based on sound. It offers concrete economic benefits, which can lead ...

    • Erratum: Adaptive boosting with SVM classifier for moving vehicle classification 

      Norasmadi, Abdul Rahim; Pandian, Paulraj Murugesa, Prof. Dr.; Abd Hamid, Adom, Prof. Dr. (Elsevier Ltd, 2013)
      Profoundly hearing impaired community (PHIC) cannot moderate wisely an acoustic noise ema- nated from moving vehicle in outdoor. They are not able to distinguish either type or distance of moving vehicle approaching from ...

    • Estimation of carrageenan concentration by using ultra sonic waves and back propagation neural networks 

      Prasad, Reddy; Krishnaiah, Duduku; Awang, Bono; Paulraj, Murugesa Pandiyan, Prof. Madya; Rosli, Mohd Yunus; Naveena Lakshmi (Asian Network for Scientific Information, 2010)
      The application of Artificial Neural Networks in chemical engineering field is being under immense research. One of the physical properties of every material has its own intensity to absorb the sound waves. Carrageenans ...

    • Estimation of mobile robot orientation using neural networks 

      Pandiyan, Paulraj Murugesa; R. Badlishah, Ahmad; Hema, Chengalvarayan Radhakrishnamurthy; Hashim, F. (Institute of Electrical and Electronics Engineering (IEEE), 2009-03-06)
      The computation of a mobile robot position and orientation is a common task in the area of computer vision and image processing. For a successful application, it is important that the position and orientation of a mobile ...

    • Feature based classification for classroom speech intelligibility prediction 

      M. Ridhwan, Tamjis; Sazali, Yaacob, Prof. Dr.; Pandian, Paulraj Murugesa, Prof. Dr.; Ahmad Nazri, Abdullah; Boon, Raymond Whee Heng,Prof. Dr. (IEEE Conference Publications, 2011-09)
      Education is one of the most important aspects in human life. Nowadays, a quality education not only rely on the teaching itself, but also the environment. One of the important aspects in providing an educative environment ...

    • Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders 

      Murugesa Pandian, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (SpringerLink, 2008-06-25)
      Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...

    • Feature space reduction in ethnically diverse Malaysian English accents classification 

      Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa , Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr. (IEEE Conference Publications, 2013)
      In this paper we propose a reduced dimensional space of statistical descriptors of mel-bands spectral energy (MBSE) vectors for accent classification of Malaysian English (MalE) speakers caused by diverse ethnics. Principle ...

    • Functional link PSO neural network based classification of EEG mental task signals 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Nagarajan, Ramachandran (Institute of Electrical and Electronics Engineering (IEEE), 2008-08-26)
      Classification of EEG mental task signals is a technique in the design of Brain machine interface [BMI]. A BMI can provide a digital channel for communication in the absence of the biological channels and are used to ...

    • Fuzzy based classification of EEG mental tasks for a brain machine interface 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Ramachandran, Nagarajan; Sazali, Yaacob; Abdul Hamid, Adom (Institute of Electrical and Electronics Engineers (IEEE), 2007-11-28)
      Patients with neurodegenerative diseases loose all motor movements including impairment of speech, leaving the patients totally locked-in. One possible option for rehabilitation of such patients is using a brain machine ...

    • Gesture recognition system for Kod Tangan Bahasa Melayu (KTBM) using neural network 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Hazry, Desa, Prof. Madya Dr.; Majid, W. M. R. W. A. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)
      This paper presents simple methods for translating Kod Tangan Bahasa Melayu (KTBM) into voice signal based on subject head and two hand gestures. Different gesture signs made by different subjects are captured using a USB ...

    • Highways Traffic Surveillance System (HTSS) using OpenCV 

      Zainab Nazar, Khalil Wafi; R. Badlishah, Ahmad, Prof. Madya, Dr.; Paulraj, Murugesa Pandiyan, Prof. Madya Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2010-06-22)
      Due to the traffic accidents over the last few years; the development of surveillance systems with multifunctional techniques has received increasing attention. The use of the smart camera is one solution to solve the ...