✦ LIBER ✦

An efficient algorithm for generalized random sampling

✍ Scribed by Amihood Amir; Doron Mintz

Publisher: Elsevier Science
Year: 1991
Tongue: English
Weight: 194 KB
Volume: 12
Category: Article
ISSN: 0167-8655
DOI: 10.1016/0167-8655(91)90005-7

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

An efficient and accurate algorithm for

An efficient and accurate algorithm for generating spatially-correlated random fields

✍ Fang, Jiannong ;Tacher, Laurent 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 87 KB

An Efficient Randomized Algorithm for De

An Efficient Randomized Algorithm for Detecting Circles

✍ Teh-Chuan Chen; Kuo-Liang Chung 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 444 KB

Detecting circles from a digital image is very important in shape recognition. In this paper, an efficient randomized algorithm (RCD) for detecting circles is presented, which is not based on the Hough transform (HT). Instead of using an accumulator for saving the information of the related paramete

BASIC algorithms for random sampling and

BASIC algorithms for random sampling and treatment randomization

✍ John A. Byers 📂 Article 📅 1991 🏛 Elsevier Science 🌐 English ⚖ 796 KB

Five BASIC programs to select random samples from populations or to randomize treatments are presented. Program 1 is used to obtain randomization of any number of treatments in an equal number of positions or test units for any number of replicates. Program 2 produces latin squares of any size for t

An efficient algorithm for generalized d

An efficient algorithm for generalized discriminant analysis using incomplete Cholesky decomposition

✍ Haixian Wang; Zilan Hu; Yu’e Zhao 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 626 KB

Generalized discriminant analysis (GDA) has provided an extremely powerful approach to extracting nonlinear features via kernel trick. And it has been suggested for a number of applications, such as classification problem. Whereas the GDA could be solved by the utilization of Mercer kernels, a drawb

Random selection algorithms for spatial

Random selection algorithms for spatial and temporal sampling

✍ John A. Byers 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 961 KB

Seven BASIC programs are presented that use algorithms for selection of treatments and samples in spatial and temporal contexts. Program (1) takes a natural sequence of samples (such as logs cut from a tree trunk) and divides them into groups (equal to the number of samples divided by treatments), a

Algorithms for random sampling from sing

Algorithms for random sampling from single-variate distributions

✍ Francesc Salvat 📂 Article 📅 1987 🏛 Elsevier Science 🌐 English ⚖ 850 KB