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Networked systems are common and crucial. One of the canonical problems in such systems is distributed resource allocation. From this rather broad class of problems, we consider a convex non-smooth resource allocation problem with a global resource constraint. Specifically, the objective function is separable and consists of a sum of convex functions, each associated with a node in a given network...
This paper studies the characteristic of NGA (Natural Gradient Algorithm), and propose a set of improved natural gradient blind separation algorithm by applying data preprocessing and constructing learning factor and nonlinear function. For data preprocessing we use de-mean and whitening method to preprocess original data to reduce the amount of computation during iteration in BSS (blind source separation)...
The goal of this paper is to establish a novel signal processing paradigm that enables us to find a point meeting time-variable specifications in dual domain (e.g., time and frequency domains) simultaneously. For this purpose, we define a new problem which we call adaptive split feasibility problem (ASFP). In the ASFP formulation, we have (i) a priori knowledge based convex constraints in the Euclidean...
A blind separation algorithm for restoring the original images from the blurred grayscale images is proposed, which utilizes the constrain ability of the nonholonomic natural gradient (NNG) in the independent component analysis(ICA) methods. However, the nonlinear activation function of this algorithm relates to the unavailable probability distribution of the sources closely, though it is robust to...
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