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Table of Contents
Comparison of features response in texture-based iris segmentation
Optimal allocation of FACTS devices: Classical versus metaheuristic approaches
Modelling of a spatially correlated MIMO wireless channel
Comparison of features response in texture-based iris segmentation by A. Bachoo and J-R. Tapamo
Abstract: Identification of individuals using iris recognition is an emerging technology. Segmentation of the iris texture from an acquired digital image of the eye is not always accurate -the image contains noise elements such as skin, reflection and eyelashes that corrupt the iris region of interest. An accurate segmentation algorithm must localize and remove these noise components. Texture features are considered in this paper for describing iris and non-iris regions. These regions are classified using the Fisher linear discriminant and the iris region of interest is extracted. Four texture description methods are compared for segmenting iris texture using a region based pattern classification approach: Grey Level Co-occurrence Matrix (GLCM), Discrete Wavelet Transform (DWT), Gabor Filters (GABOR) and Markov Random Fields (MRF). These techniques are evaluated according to their their true and false classifications for iris and non-iris pixels.
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Optimal allocation of FACTS devices: Classical versus metaheuristic approaches by Y. Del Valle, J. Perkel, G. K. Venayagamoorthy, R.G. Harley
Abstract: The application of optimization techniques to allocate and size FACTS devices in a power system is still under study. Currently, there is no widely accepted method since many researchers claim their methods to be better than others. This paper compares the effectiveness of classical and metaheuristic optimization approaches in a simple but realistic case study of optimal allocation of FACTS (Flexible AC Transmission System) devices, considering steady state and economic criteria. Concepts and details about the optimization process that tend to be overlooked in the literature are discussed together with some considerations about statistical analyses in the case of metaheuristic approaches.
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Modelling of a spatially correlated MIMO wireless channel by B.B. Varghese and B.T. Maharaj
Abstract: The channel capacity of a wireless communication system is greatly increased with the usage of multiple antennas at both the transmitter and receiver as long as the environment provides sufficient scattering. This paper shows a new geometric MIMO channel model that has taken the path loss parameter into account, as well as non-isotropic scattering at both ends of the radio link. Separate transmit and receive correlation functions are derived in a compact closed format, which includes some key parameters, such as distance between transmitter and receiver, antenna element spacing and degree of scattering. The capacity of the MIMO fading channel with varying number of antenna elements, distance between transmitter and receiver, various environments, varying signal to noise ratio at the receiver, varying the antenna element spacing at the transmitter and the degree of scattering at transmitter and receiver are investigated and shown for this model.
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