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The IEEE Global Conference on Signal and Information Processing (GlobalSIP) is a flagship conference of the IEEE Signal Processing Society. GlobalSIP'15 will be held in Orlando, Florida, USA, December 14-16, 2015. The conference will focus on signal and information processing with an emphasis on up-and-coming signal processing themes. The conference will feature world-class speakers, tutorials, exhibits, and sessions consisting of poster or oral presentations. Outstanding papers will be selected for Best Paper Awards or Best Student Paper Awards; a paper is eligible for a best student paper award if the first author of the paper is a student. IEEE Signal Processing Society and National Science Foundation will provide travel grants to eligible students.

This paper presents the design of an accelerated signal tracking module using a heterogeneous multi-graphics processing unit (GPU) platform for real-time global navigation satellite system (GNSS) software receiver. We also propose a load balancing method for the efficient use of the multi-GPU. The proposed method allocates the number of channels to each GPU, and the GPU generates replica signals and performs correlation with the allocated channels.

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In this talk, we present a new time domain electromagnetic tomographic imaging algorithm using coded
multiple excitation signals to reconstruct an extended object immersed in inhomogeneous medium. Three waveform encoding
techniques are developed to enable simultaneous source excitation as a way of improving computational efficiency

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The transformation of traditional energy networks to smart grids can assist in revolutionizing the energy industry
in terms of reliability, performance and manageability. However, increased connectivity of power grid assets for bidirectional communications presents severe security vulnerabilities. In this paper, we investigate Chi-square detector and cosine similarity matching approaches for attack detection in smart grids where Kalman filter estimation is used to measure any deviation from actual measurements. The cosine similarity matching approach is

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