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Approximating a signal or an image with a sparse linear expansion from an overcomplete dictionary of atoms is an extremely useful tool to solve many signal processing problems. Finding the sparsest approximation of a signal from an arbitrary dictionary is ...
The topology of large social, technical and biological networks such as the World Wide Web or protein interaction networks has caught considerable attention in the past few years (reviewed in Newman 2003), and analysis of the structure of such networks rev ...
We construct (k±1)-regular graphs which provide sequences of expanders by adding or substracting appropriate 1- factors from given sequences of k- regular graphs. We compute numerical examples in a few cases for which the given sequences are from the work ...
We introduce "derandomized" versions of the tensor product and the zig-zag product, extending the ideas in the derandomized squaring operation of Rozenman and Vadhan. These enable us to obtain graphs with smaller degrees than those obtained using their non ...
We present a general framework for studying global complete synchronization in networks of dynamical systems with asymmetrical connections. We extend the connection graph stability method, originally developed for symmetrically coupled networks, to the gen ...
We introduce a simple erasure recovery algorithm for codes derived from cascades of sparse bipartite graphs and analyze the algorithm by analyzing a corresponding discrete-time random process. As a result, we obtain a simple criterion involving the fractio ...
Institute of Electrical and Electronics Engineers2001
Approximating a signal or an image with a sparse linear expansion from an overcomplete dictionary of atoms is an extremely useful tool to solve many signal processing problems. Finding the sparsest approximation of a signal from an arbitrary dictionary is ...
Approximating a signal or an image with a sparse linear expansion from an over-complete dictionary of atoms is an extremely useful tool to solve many signal processing problems. Finding the sparsest approximation of a signal from an arbitrary dictionary is ...
The equipartition problem on an undirected graph G=(V,E), with n nodes and a system of edge weights, is to find a subset of [n/2] nodes such as the associate cut has the smallest cost. We present a polynomial algorithm to solve the equipartition problem on ...