Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order...
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Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure.
Complex human-engineered systems involve an interconnection of multiple decision makers (or agents) whose collective behavior depends on a compilation of local decisions that are based on partial information about eac...
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Complex human-engineered systems involve an interconnection of multiple decision makers (or agents) whose collective behavior depends on a compilation of local decisions that are based on partial information about each other and the state of the environment [1]-[4]. Strategic interactions among agents in these systems can be modeled as a multiplayer simultaneous-move game [5]-[8]. The agents involved can have conflicting objectives, and it is natural to make decisions based upon optimizing individual payoffs or costs.
In a two-wire full-duplex ISDN transmission unit, a transversal filter or a lookup table are generally proposed for echo cancellation. Both structures have their advantages and disadvantages. This paper presents a lit...
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In a two-wire full-duplex ISDN transmission unit, a transversal filter or a lookup table are generally proposed for echo cancellation. Both structures have their advantages and disadvantages. This paper presents a little-known intermediate solution, the multistage RAM (m- RAM), which is investigated analytically for the two most common least-mean-square (LMS) adaptive algorithms: the stochastic iteration algorithm (SIA) and the sign algorithm (SA). We try to develop a theory that covers not only these structures and algorithms but also, in general, nonbinary codes. This theory relies on a number of assumptions, the validity of which is discussed. Finally, our results are compared with computer simulations.
Generalized TLM formulations based on modified grids of 2-D shunt nodes or 3-D expanded nodes are proposed. Generalization consists of permitting flexible control of the numerical stability margin (and thus a time-ste...
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Generalized TLM formulations based on modified grids of 2-D shunt nodes or 3-D expanded nodes are proposed. Generalization consists of permitting flexible control of the numerical stability margin (and thus a time-step for a particular discretization), and of introducing enhanced models for curved boundaries. Formal equivalence between generalized TLM and FDTD algorithms based on the same grids is proved. Simple rules for transforming circuit models (from TLM to FDTD and vice versa) and for their equivalent excitation are given. It is demonstrated that the application of the generalized algorithm reduces computer resources required for the TLM analysis of a circular waveguide by an order of magnitude.
Steady-state analysis of soft-switching converters is discussed in this paper. Finding the steady-state solution of soft-switching converters by means of start-up transient simulation may involve onerous computations ...
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Steady-state analysis of soft-switching converters is discussed in this paper. Finding the steady-state solution of soft-switching converters by means of start-up transient simulation may involve onerous computations and convergence failure, because of the mix of fast and slow natural frequencies determined respectively by the presence of soft-switching Lr-Cr cells elements and bulky L-C filter elements. The numerical method proposed in this paper shows high reliability and fast convergence, thanks to the adoption of an interval analysis based technique for the detection of commutations and of a compensation theorem based technique for the analysis of commutations. Some examples of steady-state analysis of two dc-dc converters, an inverter and a power factor corrector are presented to highlight the good performances of the simulation algorithm.
This paper presents an adaptive step-size gradient adaptive filter. The step size of the adaptive filter is changed according to a gradient descent algorithmdesigned to reduce the squared estimation error during each...
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This paper presents an adaptive step-size gradient adaptive filter. The step size of the adaptive filter is changed according to a gradient descent algorithmdesigned to reduce the squared estimation error during each iteration. An approximate analysis of the performance of the adaptive filter when its inputs are zero mean, white, and Gaussian and the set of optimal coefficients are time varying according to a random-walk model is presented in the paper. The algorithm has very good convergence speed and low steady-state misadjustment. Furthermore, the tracking performance of these algorithms in nonstationary environments is relatively insensitive to the choice of the parameters of the adaptive filter and is very close to the best possible performance of the least mean square (LMS) algorithm for a large range of values of the step size of the step-size adaptation algorithm. Several simulation examples demonstrating the good properties of the adaptive filter as well as verifying the analytical results are also presented in the paper.
A new algorithm is presented for detecting graph monomorphisms for a pair of graphs. This algorithm entails a tree search based on the projections of the product graph called the net of the two graphs. It uses the min...
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A new algorithm is presented for detecting graph monomorphisms for a pair of graphs. This algorithm entails a tree search based on the projections of the product graph called the net of the two graphs. It uses the minimum number of neighbors of the projected graphs to detect infeasible subtrees. The algorithm, in comparison with that of Deo and coworkers, is more efficient in its storage space utilization and average execution time. It does not suffer from the ambiguity which arises in Deo et al.'s work when cyclic graphs are matched. Applications to attributed graph monomorphisms are included.
Processing high-resolution digital elevation models (DEMs) can be tedious due to the large size of the data. In uncertainty-aware drainage basin delineation, we apply a Monte Carlo (MC) simulation that further increas...
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Processing high-resolution digital elevation models (DEMs) can be tedious due to the large size of the data. In uncertainty-aware drainage basin delineation, we apply a Monte Carlo (MC) simulation that further increases the processing demand by two to three orders of magnitude. Utilizing graphics processing units (GPUs) can speed up the programs, but their on-chip random access memory (RAM) limits the size of the DEMs that can be processed efficiently on one GPU. Here, we present a parallel uncertainty-aware drainage basin delineation algorithm and a multinode GPU compute unified device architecture (CUDA) implementation along with scalability benchmarking. All of the computations are run on the GPUs, and the parallel processes communicate using a message-passing interface (MPI) via the host central processing units (CPUs). The implementation can utilize any number of nodes, with one or many GPUs per node. The performance and scalability of the program have been tested with a 10-m DEM covering 390,905 km2, i.e., the entire area of Finland. Performing the drainage basin delineation for the DEM with different numbers of GPUs shows a nearly linear strong scalability.
For control system analysis and design, and high-speed real-time computation, we highlight the computational formulation, properties and applications of the delta operator model of dynamic physical systems. Doubling a...
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For control system analysis and design, and high-speed real-time computation, we highlight the computational formulation, properties and applications of the delta operator model of dynamic physical systems. Doubling algorithms for reliable computation and illustrate the transfer function matrix of the delta operator model are formulated. In the fast sampling limit, the delta operator model tends to the dynamic system model. This intrinsic property of the delta operator model unifies continuous and discrete time control engineering and paves the way for the design of robust computational algorithms.
The methodology from this paper exploits fine and coarse-grained parallelism for the automated design of digital architectures for multimedia applications. Specific focus is placed on iterative algorithms, as demonstr...
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The methodology from this paper exploits fine and coarse-grained parallelism for the automated design of digital architectures for multimedia applications. Specific focus is placed on iterative algorithms, as demonstrated through a case study of the Chambolle algorithm for optical flow estimation.
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