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

Now showing items 40-59 of 114

    • 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 ...

    • 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- ...

    • Identification of vocal fold pathology based on Mel Frequency Band Energy Coefficients and singular value decomposition 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-11-18)
      Many approaches have been developed to detect the vocal fold pathology. Among the approaches, analysis of speech has proved to be an excellent tool for vocal fold pathology detection. This paper presents the Mel Frequency ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...