Browsing Conference Papers by Author "Paulraj, Murugesapandian"

Now showing items 1-13 of 13

    • Active stereo vision based system for estimation of Mobile Robot Orientation using composition matrix 

      Paulraj, Murugesapandian; Fadzilah, Hashim; R. Badlishah, Ahmad; Hema, Chengalvarayan Radhakrishnamurthy; Abdul Hamid, Adom (Universiti Malaysia Perlis, 2009-10-11)
      The computation of a mobile robot position and orientation is a common task in the area of computing vision and image processing. For a successful application, it is important that the position and orientation of a mobile ...

    • Brain machine interface based wheelchair control with minimal subject training 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Ramachandran, Nagarajan (Universiti Malaysia Perlis, 2009-10-11)
      Wheelchair control using a Brain Machine Interface based on motor imagery requires adequate subject training. In this paper we propose a new algorithm for a brain machine interface design which is implemented in real-time ...

    • Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abd Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2007-11-25)
      Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients ...

    • Brain machine interface: motor imagery recognition with different signal length representations 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2009-03-06)
      This work investigates how signal representations affect the performance of a motor imagery recognition system, specifically we investigate on recognition accuracy and computational time of a brain machine interface designed ...

    • Brain signatures: a modality for biometric authentication 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Kaur, Harkirenjit (Institute of Electrical and Electronics Engineering (IEEE), 2008-12-01)
      In this paper we investigate the use of brain signatures as a possible biometric authentication technique. Research on brain EEG signals has shown that individuals exhibit unique brain patterns for similar tasks. In this ...

    • Color recognition algorithm using a neural network model in determining the ripeness of a Banana 

      Paulraj, Murugesapandian; Hema, Chengalvarayan Radhakrishnamurthy; R. Pranesh, Krishnan; Siti Sofiah, Mohd Radzi (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. ...

    • 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 ...

    • Intelligent vehicle fault diagnosis system using Neural Networks 

      Paulraj, Murugesapandian; Sazali, Yaacob; Nor Shaifudin, Abd Hamid; Hema, Chengalvarayan Radhakrishnamurthy (Universiti Teknologi MaraFaculty of Electrical Engineering, 2007-03-09)
      Diagnosis has become a very complex and critical task in determining the condition of vehicle engine. Sound emitted by the engine is always considered to be an annoying noise but a detaiedl analysis of the sound signal ...

    • Malaysian vowel recognition based on spectral envelope using bandwidth approach 

      Fadzilah, Siraj; Shahrul Azmi, M. Y.; Paulraj, Murugesapandian; Sazali, Yaacob (Institute of Electrical and Electronics Engineering (IEEE), 2009-05-25)
      Automatic speech recognition (ASR) has made great strides with the development of digital signal processing hardware and software especially using English as the language of choice. In this paper, a new feature extraction ...

    • Neuro-Fuzzy based motor imagery classification for a four class brain machine interface 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Ramachandran, Nagarajan (Universiti Malaysia Perlis, 2009-10-11)
      Brain Machine Interface (BMI) provides a digital link between the brain and a device such as a computer, robot or wheelchair. This paper presents a BMI design using Neuro-Fuzzy classifiers for controlling a wheelchair using ...

    • PID and adaptive predictive fuzzy logic controller for a micro-satellite 

      Ramachandran, Nagarajan; Paulraj, Murugesapandian; Sazali, Yaacob; Zuriadah, Mat Zain; Hoh, W. S. K.; Ahmad Sabirin, Arshad (Institute of Electrical and Electronics Engineering (IEEE), 2008-12-01)
      In this paper a simple Adaptive Predictive Fuzzy Logic Controller is developed for the attitude control of a micro-satellite; its performance is compared with a PID controller. PID controller is the most widely used among ...

    • Recognition of motor imagery of hand movements for a BMI using PCA features 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abd Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2008-12-01)
      Motor imagery is the mental simulation of a motor act that includes preparation for movement and mental operations of motor representations implicitly or explicitly. The ability of an individual to control his EEG through ...

    • Single trial motor imagery classification for a four state brain machine interface 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2009-03-06)
      Motor imagery is the mental simulation of a motor act which can be used to design brain machine interfaces [BMI]. A BMI is a digital communication system, which connects the human brain directly to an external device ...