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In this paper, we apply statistical mechanics methods to the problem of detection of multiple primary wireless sources by a wireless sensor network. We assume that the location of the primary sources is known, but that the channel connecting them to the sensors is random. The sensor network tries to detect which sources are emitting by employing a belief propagation algorithm. We use the Replica approach...
Dynamic deployment aims at enhancing coverage in wireless sensor networks by redistributing sensor nodes after initial random deployment. In this paper, a harmony search based dynamic deployment (HS-DD) technique is proposed that aims at maximizing both network coverage and connectivity. Furthermore, the performance of the proposed algorithm and a number of the HS-variants in dynamic deployment is...
Localization is a fundamental challenge for any wireless network of nodes, in particular when the nodes are mobile. For an anchorless network of mobile nodes, we present a relative velocity estimation algorithm based on multidimensional scaling. We propose a generalized two-way ranging model, where the time-varying pairwise distances between the nodes are expressed as a Taylor series for a small observation...
As the processing and transport capacity of the information and communication technologies (ICT) infrastructure increased vastly the last few years, the bottleneck of the information exchange process moved to the end points of the process, i.e. the consumers and the producers of information. On one hand there is the limited time that a consumer has to access the information and on the other hand there...
This paper presents an on-line approach for optimizing paths for a pursuit-evasion problem, in which an agent must visit several target positions within an environment while simultaneously avoiding one or more actively-pursuing adversaries. This problem is found in a variety of fields, such as robotic path planning, mobile-sensor applications, and path exposure. The methodology developed utilizes...
In this paper, we propose an incremental orthogonal projective non-negative matrix factorization algorithm (IOPNMF), which aims to learn a parts-based subspace that reveals dynamic data streams. There exist two main contributions. Firstly, our proposed algorithm can learn parts-based representations in an online fashion. Secondly, by using projection and orthogonality constrains, our IOPNMF algorithm...
A local-area based fingerprint minutiae vicinity can be represented in a self-aligned way and achieves better robustness for recognition than a global minutiae template whose global geometric references (e.g., core or delta) are usually unstable to locate. However, local comparison based on vicinities ignores the global topology and thus still has potential to improve in performance if some stable...
For target tracking in Interference Environments of cognitive radar problem, Extended Karman, Particle filter algorithms etc. are generally used to be regarded as usual solutions to state estimation. Many techniques have been developed to improve performance of target tracking. In this paper, we set the structure and key features of target's tracking design for cognitive radar, and newly propose cognitive...
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