A wavelet-extreme learning machine for low-cost INS/GPS navigation system in high-speed applications-Reference-Cited by-同舟云学术

A wavelet-extreme learning machine for low-cost INS/GPS navigation system in high-speed applications

Published:2017-11-15 Issue:1 Volume:22 Page:
ISSN:1080-5370
Container-title:GPS Solutions
language:en
Short-container-title:GPS Solut

Author:

Abdolkarimi E. S.,Abaei G.,Mosavi M. R.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

http://link.springer.com/article/10.1007/s10291-017-0682-x/fulltext.html

Reference24 articles.

1. Aggarwal P (2010) MEMS-based integrated navigation. Artech House, Norwood

2. Chiang KW (2004) INS/GPS integration using neural networks for land vehicular navigation applications. University of Calgary, UCGE reports, no. 20209

3. Chiang KW, Chang HW (2010) Intelligent sensor positioning and orientation through constructive neural network-embedded INS/GPS integration algorithms. Sensors 10:9252–9285

4. El-Shafie A, Najah A, Karim OA (2014) Amplified wavelet-ANFIS-based model for GPS/INS integration to enhance vehicular navigation system. Neural Comput Appl 24:1905–1916

5. El-Sheimy N, Chiang KW, Noureldin A (2006) The utilization of artificial neural networks for multisensor system integration in navigation and positioning instruments. IEEE Trans Instrum Meas 55:1606–1615

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