sparse

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sparse

A sparse matrix (or vector, or array) is one in which most of the elements are zero. If storage space is more important than access speed, it may be preferable to store a sparse matrix as a list of (index, value) pairs or use some kind of hash scheme or associative memory.
This article is provided by FOLDOC - Free Online Dictionary of Computing (foldoc.org)
References in periodicals archive ?
Distributed compressive sensing (DCS) [6] theory has been developed to jointly reconstruct the set of sparse signals by exploiting their joint sparsity. A set of sparse signals exhibit joint sparsity, which is characterized by that the non-zero elements in each signal vector have the same location indices but different values.
Impact of variations in channels' sparsity level and training to information power ratio on normalized channel mean square error (NCMSE) is thoroughly studied.
First, by exploiting the joint sparsity model, the polarimetric TWRI formation problem is formulated as the group sparse basis pursuit denoising (BPDN) problem, which is solved by the spectral projection gradient L1-norm (SPGL1) algorithm [10, 11].
The algorithm can make the compressive ratio adjusted adaptively according to the signal sparsity, which can reduce the sampling number, but this method still needs to reconstruct the original signal.
Supposing an n-dimensional signal y = ([y.sub.1], [y.sub.2], ..., [y.sub.n])T can be represented on a basis [PSI] [member of] [R.sup.n x n] as y = [PSI]x, where x = [([x.sub.1], [x.sub.2], ..., [x.sub.n]).sup.T], if there are only K nonzero elements in x = [([x.sub.1], [x.sub.2], ..., [x.sub.n]).sup.T], y is called K - sparse signal with sparsity K, and the positions of nonzero elements in x are called the support set, which can be denoted as E = {1 [less than or equal to] i [less than or equal to] n|[x.sub.i] [not equal to] 0}.
As shown in Figures 1(c) and 1(d), the threshold for binary matrices of two groups was at a fixed sparsity of 21% (refer to Section 3.2 for threshold selection).
As Theorem 3 below reveals, the sparsity (9) of the proposed attack vector satisfies [[parallel][a.sub.i][parallel].sub.0] = [absolute value of [S.sub.i]] = k.
The core plan of this project is to recover the novel recommendation model in order to reduce the data sparsity and cold start problems and their degradation of recommendation performance, improving the data utility by neighborhood sharing maintaining the security and privacy concerns.
What then, is the role of the evidence-based natural therapist, with a sparsity of research to support clinical decisions, in a complex multisystemic health condition?