Parallel Random Walk for P/G Analysis

2013 ◽  
Vol 427-429 ◽  
pp. 2787-2790
Author(s):  
Jun Guo ◽  
Cang Song Zhang ◽  
Jiao Cui
Keyword(s):  
Parallel Computing ◽  
Random Walk ◽  
Execution Time ◽  
Time Complexity ◽  
Formal Model ◽  
Power Grid ◽  
Random Walk Algorithm ◽  
Main Factors ◽  
Parallel Features ◽  
Walk Algorithm

This paper introduced parallel computing techniques to improve random walk algorithm. The random walk problem was firstly explained by a formal model. And then, the parallel features of random walk algorithm were discussed in detail. A parallel random walk algorithm was proposed and applied to analyze the VLSI power grid. The time complexity and the main factors impacting on the execution time of algorithm were analyzed carefully. The experimental results proved that the parallel computing techniques could improve random walk algorithm effectively.

Parallel two step random walk algorithm to analyze VLSI power grid networks

2015 ◽  
Author(s):  
Satyabrata Dash ◽  
Vivek Bangera ◽  
Vinay B. Y. Kumar ◽  
Gaurav Trivedi ◽  
Sachin B. Patkar
Keyword(s):  
Random Walk ◽  
Power Grid ◽  
Grid Networks ◽  
Random Walk Algorithm ◽  
Power Grid Networks ◽  
Walk Algorithm

Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm

2014 ◽  
Vol 38 (8) ◽  
pp. 753-763 ◽  
Author(s):  
D.P. Onoma ◽  
S. Ruan ◽  
S. Thureau ◽  
L. Nkhali ◽  
R. Modzelewski ◽  
...  
Keyword(s):  
Random Walk ◽  
Fdg Pet ◽  
Random Walk Algorithm ◽  
Locally Adaptive ◽  
Walk Algorithm

AN IMPROVED RANDOM WALK SEGMENTATION ON THE LUNG NODULES

2013 ◽  
Vol 06 (06) ◽  
pp. 1350043 ◽  
Author(s):  
LI GUO ◽  
YUNTING ZHANG ◽  
ZEWEI ZHANG ◽  
DONGYUE LI ◽  
YING LI
Keyword(s):  
Random Walk ◽  
Lung Nodule ◽  
Texture Feature ◽  
Ellipse Fitting ◽  
Lung Nodule Detection ◽  
Random Walk Algorithm ◽  
Fitting Algorithm ◽  
Nodule Detection ◽  
Walk Algorithm ◽  
Automatic Technique

In this paper, we proposed a semi-automatic technique with a marker indicating the target to locate and segment nodules. For the lung nodule detection, we develop a Gabor texture feature by FCM (Fuzzy C Means) segmentation. Given a marker indicating a rough location of the nodules, a decision process is followed by applying an ellipse fitting algorithm. From the ellipse mask, the foreground and background seeds for the random walk segmentation can be automatically obtained. Finally, the edge of the nodules is obtained by the random walk algorithm. The feasibility and effectiveness of the proposed method are evaluated with the various types of the nodules to identify the edges, so that it can be used to locate the nodule edge and its growth rate.

Sign in / Sign up

Export Citation Format

Share Document