Browsing Hariharan Muthusamy, Dr. by Issue Date
Now showing items 1-20 of 77
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Prediction of Reverberation time in university classrooms using Neural Network
(Universiti Kebangsaan Malaysia, 2007)Reverberation time is fundamental to the study of the acoustics of an enclosed space. An important objective of architectural acoustics is to predict the reverberation time in an enclosed space. Reverberation time is also ... -
Application of feedforward neural network for the classification of pathological voices
(Universiti Teknologi MARA (UiTM), 2007-03-09)This paper present the application of feed forward neural network for the classification of pathological voices based on the on the acoustic analysis and EGG features. Acoustic analysis is a non-invasive technique based ... -
Identification of vocal and voice disorders
(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- ... -
Improved back propagation neural network for the diagnosis of pathological voices
(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 ... -
Automatic detection of voice disorders using self loop architecture in back propagation network
(Anna University, 2008-01-04)Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice ... -
Neural network based detection of voice disorders using energy spectrum and equal-loudness contours
(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
(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 ... -
Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders
(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 ... -
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. ... -
Design and development of stereo motion for mobile observation center
(Universiti Malaysia Perlis, 2009-10-11)This paper presents an approach to the condition monitoring patient in ICU. A human-computer interface (HCI) system is designed for the people with severe disabilities. For the last decades, most of the patients’ sleeps ... -
Artificial neural network for the classification of steel hollow pipe
(Universiti Malaysia Perlis, 2009-10-11)Within industry, piping is a very important system that used to convey fluid (liquid and gases) from one location to another. Steel pipe is one of the commonly type of pipe that has been used since before. Crack on pipe ... -
MFCC based recognition of repetitions and prolongations in stuttered speech using k-NN and LDA
(Institute of Electrical and Elctronics Engineering (IEEE), 2009-11-16)Stuttering is a speech disorder in which the normal flow of speech is disrupted by occurrences of dysfluencies, such as repetitions, interjection and so on. There are a high proportion of repetitions and prolongations in ... -
Identification of vocal fold pathology based on Mel Frequency Band Energy Coefficients and singular value decomposition
(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 ... -
Nano-satellite Attitude Control System
(Universiti Malaysia Perlis (UniMAP)Pejabat Timbalan Naib Canselor (Penyelidikan dan Inovasi), 2009-12)A satellite maneuvers through orbit with the use of an attitude control system (ACS) to stay on course and always pointing towards earth reference. This maximizes the solar cell-sun and camera-earth coverage, a process ... -
Automatic detection of prolongations and repetitions using LPCC
(Institute of Electrical and Elctronics Engineering (IEEE), 2009-12-14)Stuttering is a speech disorder in which the normal flow of speech is disrupted by occurrences of dysfluencies, such as repetitions, interjection and so on. There are high proportion of repetitions and prolongations in ... -
Time-domain features and probabilistic neural network for the detection of vocal fold pathology
(Universiti Malaya, 2010)Due to the nature of job, unhealthy social habits and voice abuse, 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. ... -
Comparison of performance using Daubechies Wavelet family for facial expression recognition
(Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)This paper investigates the performance of a Daubechies Wavelet family in recognizing facial expressions. A set of luminance stickers were fixed on subject's face and the subject is instructed to perform required facial ... -
Detection of facial changes for hospital ICU patients using neural network
(Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)This paper presents an integrated system for detecting facial changes of patient in a hospital in Intensive Care Unit (ICU). The facial changes are most widely represented by eyes movements. The proposed system uses color ...