Abstract
A wireless sensor network (WSN) consists of low-cost and energy-limited sensors to measure a distributed phenomenon. The finite energy constraint limits the synchronization of sensors at every sampling instant which introduces sampling jitters. In this letter, we model sampling jitters using fractional delay transfer functions. The WSN is modeled using a hybrid multirate filter bank where the objective is to design discrete-time, causal and stable synthesis filters to minimize the effect of sampling jitters. Using a norm-invariant discretization, the hybrid and multirate problem is reduced to a model-matching H2 optimization problem involving linear time-invariant and discrete-time systems. A numerical example is also presented to show the effectiveness of the proposed approach.
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