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This paper presents a distributed architecture for asynchronously implementing a class of nonlinear signal processing systems as web services, which in turn can be used to solve a broad class of optimization problems. As opposed to requiring specialized servers, the presented architecture requires only the use of commodity database backends as a central resource, as might typically be used to serve...
This paper presents a framework for designing a class of distributed, asynchronous optimization algorithms, realized as signal processing architectures utilizing various conservation principles. The architectures are specifically based on stationarity conditions pertaining to primal and dual variables in a class of generally nonconvex optimization problems. The stationarity conditions, which are closely...
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