Zeliang Wang

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The blue shark Prionace glauca is the most abundant large pelagic shark in the Atlantic Ocean. Although recaptures of tagged sharks have shown that the species is highly migratory, migration pathways towards the overwintering grounds remain poorly understood. We used archival satellite pop-up tags to track 23 blue sharks over a mean period of 88 days as(More)
Drought is one of the main environmental factors limiting tree growth and productivity of plantation forests worldwide. Populus hopeiensis Hu et Chow is one of the most important commercial plantation tree species in China. However, the genes controlling drought tolerance in this species have not been identified or characterized. Here, we conducted(More)
In this paper, we present an improved version of the second order sequential best rotation algorithm (SBR2) for polynomial matrix eigenvalue decomposition of para-Hermitian matrices. The improved algorithm is entitled multiple shift SBR2 (MS-SBR2) which is developed based on the original SBR2 algorithm. It can achieve faster convergence than the original(More)
—A novel multichannel spectral factorization algorithm is illustrated in this paper. This new algorithm is based on an iterative method for polynomial eigenvalue decomposition (PEVD) called the second order sequential best rotation (SBR2) algorithm [1]. By using the SBR2 algorithm, multichannel spectral factorization problems are simply broken down to a set(More)
Polynomial matrix singular value decomposition (PSVD) plays a very important role in broadband multiple-input multiple-output (MIMO) systems. It can be used to decompose a broadband MIMO channel matrix in order to recover the transmitted signals corrupted by the channel interference (CI) at the receiver. In this paper, a novel algorithm, known as multiple(More)
In this work we present a new method of controlling the order growth of polynomial matrices in the multiple shift second order sequential best rotation (MS-SBR2) algorithm which has been recently proposed by the authors for calculating the polynomial matrix eigenvalue decomposition (PEVD) for para-Hermitian matrices. In effect, the proposed method(More)
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