1) sparse polynomial
稀疏多项式
1.
It s is very effective for a class of sparse polynomials.
由多项式结构的稀疏性,此算法更能有效处理稀疏多项式。
2.
Eigenvalue matrix for resolving sparse polynomial equations is constructed by deploying well arranged basis in semigroup algebra k[A].
本文利用半群代数k[A]中良序基,构造了求稀疏多项式方程组解的特征值矩阵,并给出了可以构造方阵的条件。
3.
This paper constructs the Eigenvalue Matrix of sparse polynomial equations by means of Gr?bner bases in semigroup algebra k[A] .
利用半群代数 k[A]中 Gr?bner 基,构造了求稀疏多项式方程组解的特征值矩阵。
2) sparse mode multicast
稀疏模式多播
3) Sparse multifiber
稀疏多纤
4) sparse mode
稀疏模式
1.
Existing intra-group forwarding state reduction approaches for sparse mode multicast, which aim to remove forwarding states at non-branching routers, are analyzed, and some problems appearing in these schemes are presented.
分析了已有的用于稀疏模式组播的转发状态组内压缩方案存在的问题,提出了一个新的压缩方案。
5) sparse multi-path channel
稀疏多径信道
6) sparse multi-fibre link configuration
稀疏多光纤配置
1.
Since wavelength converters are expensive devices,we propose a sparse multi-fibre link configuration algorithm to improve the performance of networks without wavelength converters.
针对波分复用(WDM)光网络在实现端到端业务链接时的波长连续性限制问题,提出了对光网络进行稀疏多光纤配置的方法。
补充资料：多项式乘多项式法则
Image:1173836820929048.jpg
多项式乘多项式法则
先用一个多项式的每一项乘以另一个多项式的每一项，再把所得的积相加。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。