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Dynamic Diffusion Estimation in Exponential Family Models
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DOI：10.1109/LSP.2013.2282042.png)
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Abstract
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This letter proposes a new dynamic diffusion estimation method for a collaborative inference of a common model parameter using a distributed network of cooperating nodes. Unlike the existing single problem-oriented diffusion methods, it is formulated abstractly for the exponential family of models. The resulting advantage-its easy and straightforward application to the family members-is demonstrated on three selected cases: i) the diffusion autoregression, ii) the diffusion Poisson modelling and iii) the diffusion estimation of a Bernoulli process with unknown proportions. The first case is shown to coincide with the diffusion recursive least squares.
Keywords:
Diffusion estimation
distributed estimation
parameter estimation
sensor networks
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