Adithya M. Devraj

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In this work, we address the problem of finding optimal transmit power control policies for wireless energy harvesting sensors (EHS) with automatic repeat request (ARQ)-based packet (re)transmissions. The policy is designed to minimize the average probability of packet outage, under the constraint of long-term energy neutrality at the EH node. The indirect(More)
The feedback particle filter (FPF) is an approach to estimating the posterior distribution of the states in a process-observation model. As in other versions of the particle filter, Monte Carlo methods are used to generate and propagate a set of particles, based on the underlying model. The system is designed so that the empirical distribution of the(More)
The problem of estimating the complex amplitude of a signal which is known only to an unknown scaling factor with noise present is a well studied problem. Maximum likelihood (ML) and Capon estimates of the complex amplitude in the case where the noise vectors are circularly symmetric complex Gaussian with an unknown arbitrary covariance matrix have been(More)
<lb>The Zap Q-learning algorithm introduced in this paper is an improvement of Watkins’ origi-<lb>nal algorithm and recent competitors in several respects. It is a matrix-gain algorithm designed<lb>so that its asymptotic variance is optimal. Moreover, an ODE analysis suggests that the tran-<lb>sient behavior is a close match to a deterministic(More)
Value functions arise as a component of algorithms as well as performance metrics in statistics and engineering applications. Computation of the associated Bellman equations is numerically challenging in all but a few special cases. A popular approximation technique is known as Temporal Difference (TD) learning. The algorithm introduced in this paper is(More)
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