This page provides access to research works by Assoc. Prof. Dr. Paulraj Murugesa Pandiyan, currently a Professor of School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP).

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Skills and Expertise: Neural Network, Fuzzy Logic, Signal Processing and Image Processing

Recent Submissions

  • Malaysian English accents identification using LPC and formant analysis 

    Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr.; Saidatul, A. (IEEE Conference Publications, 2011-11)
    In Malaysia, most people speak several varieties of English known as Malaysian English (MalE) and there is no uniform version because of the existence of multi-ethnic population. It is a common scenario that Malaysians ...
  • Speaker accent recognition through statistical descriptors of Mel-bands spectral energy and neural network model 

    Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr.; Nataraj, Sathees Kumar (IEEE Conference Publications, 2012-10)
    Accent recognition is one of the most important topics in automatic speaker and speaker-independent speech recognition (SI-ASR) systems in recent years. The growth of voice-controlled technologies has becoming part of our ...
  • Classification of speaker accent using hybrid DWT-LPC features and K-nearest neighbors in ethnically diverse Malaysian English 

    Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr. (IEEE Conference Publications, 2012-12)
    Accent is a major cause of variability in automatic speaker-independent speech recognition systems. Under certain circumstances, this event introduces unsatisfactory performance of the systems. In order to circumvent this ...
  • 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 ...
  • Motorbike engine faults diagnosing system using neural network 

    Paulraj, Murugesa Pandiyan, Prof. Dr.; Mohd Shukry, Abdul Majid, Dr.; Sazali, Yaacob, Prof. Dr.; Zin, M.Z.M. (IEEE Conference Publications, 2008-12)
    Monitoring systems for motorbike industry requires high and efficient degree of performance. In recent years, automatic identification and diagnosis of motorbike engine faults has become a very complex and critical task. ...
  • Application of frame energy based DCT moments for the damage diagnosis in steel plates using FLNN 

    Paulraj, Murugesa Pandiyan, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shukry, Abdul Majid, Dr.; Krishnan, Pranesh (IEEE Conference Publications, 2012-12)
    This paper discusses the application of frame energy based Discrete Cosine Transformation (DCT) moment features for the detection of damages in steel plates. A simple experimental model is devised to suspend the steel ...
  • Steel plate damage diagnosis using probabilistic neural network 

    Paulraj, Murugesa Pandiyan, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shukry, Abdul Majid, Dr.; Krishnan, Pranesh (IEEE Conference Publications, 2013-01)
    This paper discusses the application of frame energy based DFT spectral band features for the detection of damages in steel plates. A simple experimental model is devised to suspend the steel plates in a free-free condition. ...
  • Structural steel plate damage detection using non destructive testing, frame energy based statistical features and artificial neural networks 

    Pandiyan, Paulraj Murugesa , Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shukry, Abdul Majid, Dr.; Mohd Nor Fakhzan, Mohd Kazim; Krishnan, Pranesh (Elsevier Ltd., 2013)
    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 ...
  • 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) ...
  • Brain machine interface for physically retarded people using colour visual tasks 

    Pandiyan, Paulraj Murugesa, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr.; Hema, Chengalvarayan Radhakrishnamurthy; Purushothaman, D. (IEEE Conference Publications, 2010-05)
    A Brain Machine Interface is a communication system which connects the human brain activity to an external device bypassing the peripheral nervous system and muscular system. It provides a communication channel for the ...
  • 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 ...
  • 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 ...
  • Statistical formant descriptors with linear predictive coefficients for accent classification 

    Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa , Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr.; Nor Fadzilah, Mokhtar (Institute of Electrical and Electronics Engineers (IEEE), 2013-06)
    Accent is a special trait of human speech that can deliver some information about a speaker's background. At the same time it is one of the profound factors that affects the intelligibility and performance of speech ...
  • Implementing eigen features methods/neural network for EEG signal analysis 

    Saidatul Ardeenawatie, Awang; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2013-01)
    This paper presented the possibility of implementing eigenvector methods to represent the features of electroencephalogram signal. In this study, three eigenvector methods were investigated namely Pisarenko, Multiple Signal ...
  • Moving vehicle detection using time domain statistical features 

    Paulraj, Murugesa Pandiyan, Prof. Dr.; Abd Hamid, Adom, Prof. Dr.; Siti Marhainis, Othman; Sathishkumar, Sundararaj (Trans Tech Publications, 2014)
    The Hearing Impaired People (HIP) cannot distinguish the sound from a moving vehicle approaching from their behind. Since, it is difficult for hearing impaired to hear and judge sound information and they often encounter ...
  • 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 ...
  • Classification of acoustic sound signature of moving vehicle using artificial neural network 

    Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Prof., Dr.; Sathishkumar, Sundararaj (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
    The hearing impaired is afraid of walking along a street and living a life alone. Since, it is difficult for hearing impaired to hear and judge sound information and they often encounter risky situations while they are in ...
  • Multi-classifier system for moving vehicles classification based on spectral bands energy 

    Norasmadi, Abdul Rahim; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Adom, Abdul Hamid, Prof. Dr.; Sathishkumar, Sundararaj (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
    Profoundly hearing impaired community cannot moderate wisely an acoustic noise emanated from moving vehicle in outdoor. They are not able to distinguish either type or distance of moving vehicle approaching from behind. ...
  • Moving vehicle recognition and classification based on time domain approach 

    Paulraj, Murugesa Pandiyan, Prof. Dr.; Abd Hamid, Adom, Prof. Dr.; Sathishkumar, Sundararaj; Norasmadi, Abdul Rahim (Elsevier Ltd, 2013)
    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 ...
  • Adaptive boosting with SVM classifier for moving vehicle classification 

    Norasmadi, Abdul Rahim; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Malaysian Technical Universities Network (MTUN), 2012-11-20)
    This study examines co-solvent modified supercritical carbon dioxide (SC-CO2) to extract the saturated fatty acids from palm oil. The applied pressure was ranging from 60 to 180 bar and the extraction temperatures were ...

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