1) Variable window search peak algorithm
可变窗谱峰搜索算法
2) spectral peak search
谱峰搜索
1.
The parallel realization of MUSIC algorithm on four TMS320C40 DSP chips is described In the procedure of realization,some effective measurements are taken to reduce the computational load,and the residues of spectral peak search in uniform circular array and linear array are proved They are favorable to reduce digital signal processing tim
在实现过程中 ,采取了一些有效的措施减少了计算量 ,指出了在均匀圆阵和均匀线阵的谱峰搜索中具有很大的计算冗余性 ,这些都有助于缩短信号处理时间。
3) variable neighborhood search algorithm
变邻域搜索算法
1.
Application of evolutionary variable neighborhood search algorithm to location-allocation problem in close-loop supply chain;
用进化变邻域搜索算法求解闭合供应链选址问题
2.
A two-stage variable neighborhood search algorithm was designed to solve the problem, and the algorithm solves the problem by optimizing the average rolling length first and optimizing hot charge rate secondly.
提出了一种两阶段变邻域搜索算法,该算法按照先优化平均单元计划轧制长度后优化热装比的顺序求解该问题。
4) variable neighborhood search
变邻域搜索算法
1.
A variable neighborhood search algorithm was presented to solve the no-wait flow shop problem with makespan criterion.
仿真实验证明了变邻域搜索算法的有效性。
2.
A new metaheuristic algorithm,the variable neighborhood search(VNS),has been successfully used to solve optimizaiton problem,especially for the largescale combinational optimization problem.
变邻域搜索算法(Variable Neighborhood Search,VNS)作为一种新的元启发式算法,已初步成功地用于解决优化问题,尤其是对于大规模组合优化问题效果良好。
5) Variable depth search algorithm
变深度搜索算法
6) search algorithm
搜索算法
1.
LPPDS:line prediction based pseudo-diamond search algorithm;
LPPDS:基于线性预测的准菱形搜索算法
2.
Cross-word search algorithm based on two-layer lexical tree for speech recognition;
语音识别中基于两层词法树的跨词搜索算法
补充资料：谱窗
谱窗
spectral window
谱窗〔s碑ctrai雨l‘附;c“留p呱Hoe。口o]，谙密度估计量的 角频率几的函数，用来在平稳随机过程(stat玩-娜stochastic plocess)X(t)的谱密度(spectral山姐-sity)f(又)的非参数估计中定义一个权函数，以光滑从该过程的观测数据构造的周期圈(peri(月09知m).作为谱密度在一点又。处的值的估计，通常取在又的周期图与一形如BNA(B、(又一又。))的表达式之积对d又的积分，其中B、是一个实数而A(幻是频率的确定函数，它在几=O处取其最大值且关于又的积分等于1.这个函数通常称为谱窗生成元(spectrai俪n-dow generator)，而“谱窗”一词则用来称呼函数B、A(B，劝.谱窗的宽度为B粼，它依赖于样本容量N(即过程X(t)的被观测实现的长度)且当N~的时趋于零(但比N一，要慢).谱窗的Fourier变换(在离散时间t的情形下，一兀毛又<兀，则是其Fourier系数的集)称为谱密度估计的滞后窗(吨俪n-dow).它定义一个离散或连续自变量(依赖于t为离散或连续)的权函数，由它乘以从给定样本算出的样本自相关函数，其所得乘积的Four记r变换即为所要求的谱密度估计t(speetrai density，estin祖torof1」le).
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条