P300 Wave based Person Identification using LVQ Neural Network

نویسندگان

  • Xin Yang
  • Jianhua Dai
  • Huaijian Zhang
  • Bian Wu
  • Yu Su
  • Weidong Chen
  • Xiaoxiang Zheng
چکیده

Person identification technology has many applications. It has been shown in previous studies that the brain-wave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for person identification. In this paper, a kind of event related potential-P300, is employed as the input of the identification system. Compared with the other EEG signal, the P300 wave is easier for the classifier to tell the difference between diverse individuals. Learning vector quantization (LVQ) neural network is used for the classifier to identify which individual the P300 wave belongs to. Moreover, a voting scheme is introduced into the identification process which significantly improves the identification performance.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

High Impedance Fault Detection using LVQ Neural Networks

This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from ...

متن کامل

طبقه بندی و شناسایی رخساره‌های زمین‌شناسی با استفاده از داده‌های لرزه نگاری و شبکه‌های عصبی رقابتی

Geological facies interpretation is essential for reservoir studying. The method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. Use of neural networks as classifiers is increasing in different sciences like seismic. They are computer efficient and ideal for patterns identification. They can simply learn new algori...

متن کامل

Evaluation of the Hidden Markov Model for Detection of P300 in EEG Signals

Introduction: Evoked potentials arisen by stimulating the brain can be utilized as a communication tool  between humans and machines. Most brain-computer interface (BCI) systems use the P300 component,  which is an evoked potential. In this paper, we evaluate the use of the hidden Markov model (HMM) for  detection of P300.  Materials and Methods: The wavelet transforms, wavelet-enhanced indepen...

متن کامل

Load Identification in Neural Networks for a Non-intrusive Monitoring of Industrial Electrical Loads

This paper proposes the use of neural network classifiers to evaluate back propagation (BP) and learning vector quantization (LVQ) for feature selection of load identification in a non-intrusive load monitoring (NILM) system. To test the performance of the proposed approach, data sets for electrical loads were analyzed and established using a computer supported program Electromagnetic Transient...

متن کامل

Iris Recognition Based on LBP and Combined LVQ Classifier

Iris recognition is considered as one of the best biometric methods used for human identification and verification, this is because of its unique features that differ from one person to another, and its importance in the security field. This paper proposes an algorithm for iris recognition and classification using a system based on Local Binary Pattern and histogram properties as a statistical ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011