The main purpose of this paper is to study weight-semi-greedy Markushevich bases, and in particular, find conditions under which such bases are weight-almost greedy. In context, we prove that, for a large class weights, the two notions equivalent. We also show that all weight semi-greedy truncation quasi-greedy weight-superdemocratic. above cases, bring context weights weak greedy Chebyshev alg...

We continue with the study of greedy-type bases in quasi-Banach spaces started [3]. In this paper, we partially-greedy focusing our attention two main results: -Characterization terms quasi-greediness and different conservative-like properties. -Given a $C$-partially-greedy basis space, there exists renorming such that is $1$-partially-greedy.

We present a new approach known as greedy segmentation (GS) to identify multiple changepoints for functional data sequence. The proposed changepoint detection criterion links detectability with the projection onto suitably chosen subspace and locations. estimator identifies true any predetermined number of candidates, either over-reporting or under-reporting. This theoretical finding supports G...

In 2003, S. J. Dilworth, N. Kalton, D. Kutzarova and V. Temlyakov introduced the notion of almost greedy (respectively partially greedy) bases. These bases were characterized in terms quasi-greediness democracy conservativeness). this paper, we show a new functional characterization these type general Banach spaces following spirit greediness proved 2017 by P. M. Berná Ó. Blasco.

—We consider a (phylogenetic) tree with n labeled leaves, the taxa, and a length for each branch in the tree. For any subset of k taxa, the phylogenetic diversity is defined as the sum of the branch-lengths of the minimal subtree connecting the taxa in the subset. We introduce two time-efficient algorithms (greedy and pruning) to compute a subset of size k with maximal phylogenetic diversity in...

In this paper we classify the greedy routing in sensor networks into two categories, strong greedy routing and weak greedy routing. Most existing work mainly focuses on weak greedy routing over geographic location network or strong greedy routing over greedy embedding network. It is a difficult job and needs much cost to obtain geographic location or greedy embedding of the network. We propose ...

This paper addresses the optimization problem of managing research efforts a set sensors in order to minimize probability non-detection target. A novel formulation taking into account traveling costs between searched areas is proposed; it more realistic and extends some previous problems addressed literature. greedy heuristic algorithm devised, builds solution gradually, using linear approximat...

introduction several methods have been developed to aid in selecting a network of biodiversity protected areas. one of these methods is artificial intelligence which includes a number of different computer algorithms that use an objective function to find the best solution. an algorithm is a mathematical process or a set of rules used for problem solving. recently, site selection algorithms hav...