Improved Low Time-Complexity Schedulability Test for Non-Preemptive EDF on a Multiprocessor

2021 ◽  
pp. 1-1
Author(s):  
Seongtae Lee ◽  
Sanghyeok Park ◽  
Jinkyu Lee
Keyword(s):  
Time Complexity ◽  
Schedulability Test

Recognition of Birds in Blurred and Illumination Images by Local Features

2017 ◽  
Vol 7 (7) ◽  
pp. 243
Author(s):  
Suresha .M ◽  
. Sandeep
Keyword(s):  
Computer Vision ◽  
Time Complexity ◽  
Feature Detection ◽  
Feature Matching ◽  
Fast Algorithms ◽  
Local Features ◽  
Experimental Demonstration ◽  
Harris Corner ◽  
Blurred Image ◽  
Blurred Images

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.

Schedulability Test for Multiprocessor Scheduling Based on Hyperbolic Bound

2012 ◽  
Vol 23 (8) ◽  
pp. 2223-2234
Author(s):  
Hong-Ya WANG ◽  
Wei YIN ◽  
Hui SONG ◽  
Lih-Chyun SHU ◽  
Mei WANG
Keyword(s):  
Multiprocessor Scheduling ◽  
Schedulability Test

On the time complexity of worst-case system identification

1994 ◽  
Vol 39 (5) ◽  
pp. 944-950 ◽  
Author(s):  
K. Poolla ◽  
A. Tikku
Keyword(s):  
System Identification ◽  
Time Complexity ◽  
Worst Case ◽  
Case System

A Time Complexity Gap for Two-Way Probabilistic Finite-State Automata

1990 ◽  
Vol 19 (6) ◽  
pp. 1011-1023 ◽  
Author(s):  
Cynthia Dwork ◽  
Larry Stockmeyer
Keyword(s):  
Time Complexity ◽  
Finite State Automata ◽  
Finite State ◽  
Probabilistic Finite State Automata

Dimension-Descending Algorithm for Spherical Delaunay Triangulation

2011 ◽  
Vol 130-134 ◽  
pp. 2915-2919
Author(s):  
Ping Duan ◽  
Jia Tian Li ◽  
Jia Li
Keyword(s):  
Delaunay Triangulation ◽  
Time Complexity ◽  
Image Point ◽  
Spherical Space ◽  
Projected Image ◽  
Plane Image ◽  
Projection Center ◽  
Space Data ◽  
Construction Algorithms ◽  
Main Construction

Spherical Delaunay triangulation (SDT) which is a powerful tool to represent, organize and analyze spherical space data has become a focus of spherical GIS research. Projection stitching algorithm is one of the main construction algorithms of SDT. The basic idea of stitching algorithm is that the sphere is divided into two hemispheres to avoid projected image point coincidence. So, the practicality of projection stitching algorithm is lower because of merging two hemispheres. Aimed at the disadvantage of projection stitching algorithm, this paper puts forward a new algorithm to construct SDT used perspective projection principle. The projection center is placed on sphere to establish one-to-one mapping between spherical space points and plane image points. Experiment shows that the time complexity of our algorithm depends on Delaunay triangulation construction algorithm of the plane.

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