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In this paper, we present a new method for stochastic simulation of coupled chemical reactions. In this method we obtain recursive expressions for propagating the first two moments of the probability distributions over time. Its advantage over other simulation methods is that it does not require Monte Carlo simulations, and hence it performs several orders(More)
Accurate estimation of synchronization parameters is critical for reliable data detection in digital transmission. Although several techniques have been proposed in the literature for estimation of the reference parameters, i.e., timing, carrier phase, and carrier frequency offsets, they are based on either heuristic arguments or approximations, since(More)
Recent advances of wireless sensor networks have presented some very interesting problems for signal processing. For practical reasons , many networks are composed of simple sensors that use very little power and do not consume much communication bandwidth. A class of sensors that satisfy these requirements are the tertiary sensors. They report an(More)
An important application of sensor networks is target tracking and localization. To deal with sensor nodes with limited energy supply and communication bandwidth we propose energy-efficient hierarchical architectures for solving the target tracking problem. In these networks, sensors form clusters and transmit minimal quantized information about a sensed(More)
In this paper, we study the problem of joint model selection and parameter estimation under the Bayesian framework. We propose to use the Population Monte Carlo (PMC) methodology in carrying out Bayesian computations. The PMC methodology has recently been proposed as an efficient sampling technique and an alternative to Markov Chain Monte Carlo (MCMC)(More)
Keywords: Localization Least squares Monte Carlo methods Cramé r–Rao bounds a b s t r a c t We propose algorithms for distributed sensor self-localization using beacon nodes. These beacon nodes broadcast some information which describes their positions. The sensor nodes with unknown location information utilize these descriptions along with the(More)
In this paper we propose a novel approach for separating convolutive mixtures in the frequency domain. This approach involves the solution of several instantaneous mixing problems and the elimination of the indeterminacies which appear because the sources may be extracted in a different order or with different amplitudes in some frequency bins. In order to(More)
In this paper we consider the problem of target tracking in a network of mobile agents that receive asynchronous measurements. The agents measure received signal strengths from the target and broadcast the information to the remaining agents engaged in the tracking. We propose several non-centralized schemes based on particle filtering that account for the(More)
This paper addresses the problem of indoor tracking of tagged objects with Ultra High Frequency (UHF) Radio Frequency Identification (RFID) systems. A new and more realistic observation model of the system is proposed, where the probability of detecting a tag by a reader is described by a Beta distribution. We model the probability of detection as a(More)