Cart (Loading....) | Create Account
Close category search window
 

Novel Range-Free Localization Based on Multidimensional Support Vector Regression Trained in the Primal Space

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Jaehun Lee ; Sch. of Electr. & Electron. Eng., Yonsei Univ., Seoul, South Korea ; Baehoon Choi ; Euntai Kim

A novel range-free localization algorithm based on the multidimensional support vector regression (MSVR) is proposed in this paper. The range-free localization problem is formulated as a multidimensional regression problem, and a new MSVR training method is proposed to solve the regression problem. Unlike standard support vector regression, the proposed MSVR allows multiple outputs and localizes the sensors without resorting to multilateration. The training of the MSVR is formulated directly in primal space and it can be solved in two ways. First, it is formulated as a second-order cone programming and trained by convex optimization. Second, its own training method is developed based on the Newton-Raphson method. A simulation is conducted for both isotropic and anisotropic networks, and the proposed method exhibits excellent and robust performance in both isotropic and anisotropic networks.

Published in:

Neural Networks and Learning Systems, IEEE Transactions on  (Volume:24 ,  Issue: 7 )

Date of Publication:

July 2013

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.