Browsing Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. by Title
Now showing items 20-39 of 113
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Car cabin interior noise classification using temporal composite features and probabilistic neural network model
(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 acoustic sound signature of moving vehicle using artificial neural network
(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 ... -
Classification of EEG colour imagination tasks based BMI using energy and entropy features
(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 ... -
Classification of speaker accent using hybrid DWT-LPC features and K-nearest neighbors in ethnically diverse Malaysian English
(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 ... -
Classification of vehicle noise comfort level using feedforward neural network
(Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27) -
Classification of vowel sounds using MFCC and feed forward neural network
(Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)The English language as spoken by Malaysians varies from place to place and differs from one ethnic community and its sub-group to another. Hence, it is necessary to develop an exclusive Speech to text translation system ... -
Classroom speech intelligibility prediction using Elman neural network
(Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)A study was conducted to develop a simple system for classrooms speech intelligibility prediction. In this study, several classrooms properties such as size, signal-to-noise ratio (SNR) and Speech Transmission Index ... -
Color recognition algorithm using a neural network model in determining the ripeness of a Banana
(Universiti Malaysia Perlis, 2009-10-11)This paper presents a simple color recognition algorithm using a Neural Network model and applied to determine the ripeness of a banana. The captured image of the banana is resized and its RGB color components are extracted. ... -
Control brain machine interface for a power wheelchair
(Springer-Verlag, 2011-06-20)Controlling a power wheelchair using a brain machine interface (BMI) requires sufficient subject training. A neural network based BMI design using motor imagery of four states is used to control the navigation of a power ... -
Damage detection in steel plates using artificial neural networks
(Institute of Electrical and Electronics Engineering (IEEE), 2009-06-04)In this paper, a simple method for crack identification in steel plates based on frame energy based Discrete Cosine Transformation (DCT) is presented. A simple experimental procedure is also proposed to measure the vibration ... -
Damage detection in steel plates using discrete cosine transformation techniques and artificial neural network
(Universiti Malaysia Perlis, 2009-10-11)In this paper, a simple method for crack identification in steel plates based on the Frame Energy based Discrete Cosine Transformation [DCT] moments is presented. A simple experimental procedure is also proposed to measure ... -
Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network
(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 ... -
Determination of stress index: approach and challenges
(Universiti Malaysia Perlis, 2009-10-11)This paper discusses the preliminary study of stress detection towards determination of stress index through qualitative and quantitative evaluation of physical and psychological during stress. Awareness of stress effect ... -
Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot
(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
(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
(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
(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
(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
(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
(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) ...