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    Synchronous brain machine interface design using focused time delay networks 

    Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Ramachandran, Nagarajan, Prof. Dr. (Universiti Malaysia Perlis (UniMAP), 2012-02-27)
    Focused time delay neural network based design for a four-state Brain Machine Interface (BMI) to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively using two bipolar electrodes are used in the ...
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    Classification of EEG colour imagination tasks based BMI using energy and entropy features 

    Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Hema, Chengalvarayan Radhakrishnamurthy; Purushothaman, Divakar (Universiti Malaysia Perlis (UniMAP), 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 ...
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    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 ...
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    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 ...
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    Image quality assessment using Elman neural network model 

    Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Palaniappan, Rajkumar; Mohd Shuhanaz, Zanar Azalan (Universiti Malaysia Perlis (UniMAP), 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 ...
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    Classification of vehicle noise comfort level using feedforward neural network 

    Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Siti Marhainis; Andrew, Allan Melvin (Universiti Malaysia Perlis (UniMAP), 2012-02-27)
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    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 ...
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    BMI using spectral energy entropy for colour visual tasks 

    Divakar, Purushothaman; Paulraj, Murugesa Pandiyan, Prof. Madya Dr.; Abdul Hamid, Adom, Dr.; Hema, Chengalvarayan Radhakrishnamurthy (Universiti Malaysia Perlis (UniMAP), 2010-10-16)
    EEG signals are the electrophysiological measures of brain function and it is used to develop a Brain machine Interface. A Brain machine Interface (BMI) system is used to provide a communication and control technology ...
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    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) ...
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    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 ...
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    AuthorSazali, Yaacob, Prof. Dr. (15)Hema, Chengalvarayan Radhakrishnamurthy (7)Paulraj, Murugesa Pandiyan, Prof. Madya (5)Muthusamy, Hariharan, Dr. (4)Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. (4)... View MoreSubject
    Neural network (24)
    Acoustic analysis (4)Acoustic features (3)Brain machine interface (3)Slope parameter (3)... View MoreDate Issued2013 (1)2012 (5)2010 (5)2009 (5)2008 (6)2007 (2)

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