By B. Baranidharan, B. Shanthi (auth.), Dhinaharan Nagamalai, Eric Renault, Murugan Dhanuskodi (eds.)
This booklet constitutes the refereed court cases of the 1st foreign convention on Advances in Parallel, disbursed Computing applied sciences and functions, PDCTA 2011, held in Tirunelveli, India, in September 2011.
The sixty four revised complete papers have been conscientiously reviewed and chosen from over four hundred submissions. delivering an outstanding foreign discussion board for sharing wisdom and ends up in conception, method and purposes of parallel, dispensed computing the papers handle all present matters during this box with specified concentrate on algorithms and functions, desktop networks, cyber belief and protection, instant networks, in addition to cellular computing and bioinformatics.
Read or Download Advances in Parallel Distributed Computing: First International Conference on Parallel, Distributed Computing Technologies and Applications, PDCTA 2011, Tirunelveli, India, September 23-25, 2011. Proceedings PDF
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Extra resources for Advances in Parallel Distributed Computing: First International Conference on Parallel, Distributed Computing Technologies and Applications, PDCTA 2011, Tirunelveli, India, September 23-25, 2011. Proceedings
Varghese and M. Wilscy 18 16 FRR,FAR(%) 14 12 10 FRR 8 FAR 6 4 2 0 6000 6500 6600 6800 6900 7000 7300 7500 8000 8500 Threshold Fig. 9. False Acceptance Rate and False Rejection Rate (%) for Yale database 5 Conclusion In this paper, a new face recognition system using vector quantization based on Integrated Adaptive Fuzzy Clustering (IAFC) is developed. A simple and efficient codebook design algorithm for face recognition using vector quantization is proposed. The codebook is created from two different codebooks.
The results are more efficient than the existing method which consists of an optimized codebook with systematically organized codebook and Kohonen’s SOM. For practical applications of face recognition, not a simple recognition rate but a False Acceptance Rate (FAR) and a False Rejection Rate (FRR) are more important. Rejection rate is calculated for obtaining the FAR and FRR. 5 % and 6 % is obtained for AT & T and Yale database respectively. References 1. : Human and machine recognition of faces: a survey.
MUSIC procedures are computationally much simpler than the MLM but they provide less accurate estimate . The total number of signals impinges on the antenna array is less than the total number of receiving antenna array. 2. Inability to resolve the closely spaced signals 3. Need for the knowledge of the existing characteristics such as noise characteristics. Cyclic MUSIC algorithm overcomes the above drawbacks. It exhibits cyclostationarity, which improves the DOA estimation. Extended Cyclic MUSIC shows dramatic improvements than the Cyclic MUSIC of its extended data vector.