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The efficient sparse coding and reconstruction of signal vectors via linear observations has received a tremendous amount of attention over the last decade. In this context, the automated learning of a suitable basis or overcomplete dictionary from training data sets of certain signal classes for use in sparse representations has turned out to be of particular importance regarding practical signal...
We propose a new algorithm based on PEG algorithm to construct high-girth quasi-cyclic low-density parity check (QC-LDPC) codes. Before our improved algorithm in introduction, we depict the general algorithm based on PEG algorithm to construct QC - LDPC code, if necessary to eliminate the short cycles, that would bring in cycles-search. When code length of basic matrix is not too long, the algorithm...
SimRank has been proposed to rank web documents based on a graph model on hyperlinks. The existing techniques for conducting SimRank computation adopt an iteration computation paradigm. The most efficient technique has the time complexity O(n3) with the space requirement O(n2) in the worst case for each iteration where n is the number of nodes (web documents). In this paper, we propose novel optimization...
In this work, we present a novel adaptive filtering scheme that builds on and advances the method of joint iterative optimization (JIO) of reduced-rank filters proposed in [1]. The scheme applies the theory of error bounded set-membership filtering to both the adaptation of the bank of full-rank filters that form the projection matrix, and the reduced-rank adaptive filter that operates in the lower...
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