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This paper addresses the problem of distributed rate allocation for a class of multicast networks employing linear network coding. The goal is to minimize the cost (for example, the sum rates allocated to each link in the network) while satisfying a multic ...
Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...
We consider the problem of designing controllers for nonholonomic mobile robots converging to the source (minimum) of a field. In addition to the mobility constraints posed by the nonholonomic dynamics, we assume that the field is completely unknown to the ...
This paper addresses the problem of distributed rate allocation for a class of multicast networks employing linear network coding. The goal is to minimize the cost (for example, the sum rates allocated to each link in the network) while satisfying a multic ...
In this paper an Iterative Learning Control (ILC) algorithm is proposed for a certain class of Linear Parameter Varying (LPV) systems whose dynamics change between iterations. Consistency of the algorithm in the presence of stochastic disturbances is shown ...
An adaptive diffusion augmented complex least mean square (D-ACLMS) algorithm for collaborative processing of the generality of complex signals over distributed networks is proposed. The algorithm enables the estimation of both second order circular (prope ...
A Markov switching algorithm is introduced to classify attenuation measurements from telecommunication microwave links into dry and rainy periods. It is based on a simple state-space model and has the advantage of not relying on empirically estimated thres ...
We investigate a subband adaptive version of the popular iterative shrinkage/thresholding algorithm that takes different update steps and thresholds for each subband. In particular, we provide a condition that ensures convergence and discuss why making the ...
We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Some results about the convergen ...
The classic weighted averages (WA) algorithm for the evaluation of Sommerfeld-like integrals is reviewed and reappraised. As a result, a new version of the WA algorithm, called generalized WA, is introduced. The new version can be considered as a generaliz ...
Institute of Electrical and Electronics Engineers2012