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Adaptive networks rely on in-network and collaborative processing among distributed agents to deliver enhanced performance in estimation and inference tasks. Information is exchanged among the nodes, usually over noisy links. The combination weights that are used by the nodes to fuse information from their neighbors play a critical role in influencing the adaptation and tracking abilities of the network...
We present a growing-window variable-regularization recursive least squares (GW-VR-RLS) algorithm. Standard recursive least squares (RLS) uses a time-invariant regularization. More specifically, the inverse of the initial covariance matrix in classical RLS can be viewed as a regularization term, which weights the difference between the next state estimate and the initial state estimate. The present...
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