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java-k-best

  • 资源大小:27.48 kB
  • 上传时间:2021-06-29
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  • 资源积分:1积分
  • 标      签: javakbest

资 源 简 介

Implementation of the Murty algorithm to obtain the best K assignments. Includes the implementation of the Jonker-Volgenant algorithm. Usual applications are multiple target tracking algorithms, Joint Probabilistic Data Association (JPDA), Multiple Hypothesis Tracking (MHT), Global Nearest Neighbours (GNN), etc. Based on the original code by Jonker-Volgenant, and the Murty Matlab implementation by Eric Trautmann (http://www.mathworks.fr/matlabcentral/fileexchange/30837-k-best-assignment-algorithm). Can be used both from Java or Matlab. Time for a 100x100 assignment problem, with k=20: * Matlab implementation: 54.5 sec * Java implementation: 1 sec

文 件 列 表

java-k-best-1.00
src
com
google
code
javakbest
README.TXT
java-k-best.jar
findkbest.m
LICENSE
src
com
google
code
javakbest
Murty.java
JVC.java
PartitionNode.java
Test.java
Node.java

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