The Principal Component Analysis of Signal Characteristic Parameters

Guang Hui Li; Zheng Pei; Ran Chen; Da Li Hu

doi:10.4028/www.scientific.net/AMM.128-129.1269

Paper Titles

The End-Point Ingredient Prediction of Low Carbon Ferrochrome Smelt Based on the Working Condition
p.1246

The Model and Algorithm of Doppler Radar Speed Measurement System
p.1250

The Model and Simulation of Hydraulic Non-Sinusoidal Vibration System on Billet Caster Crystallizer
p.1257

The Optimal Attitude Controller Design and Simulation of Three-Axis Dual Rotor Helicopter
p.1265

The Principal Component Analysis of Signal Characteristic Parameters
p.1269

The Simulation Analysis of Structure Type Effect on Cutting Process
p.1273

The Simulation Analysis of Tool Orthogonal Rakes Affecting Metal Cutting
p.1277

Track Initiation Based on Extended Trellis and Randomized Hough Transform
p.1281

Wood Board Defects Sorting Based on Method of Possibilistic C-Means Improved Support Vector Data Description
p.1288

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 128-129The Principal Component Analysis of Signal...

The Principal Component Analysis of Signal Characteristic Parameters

Abstract:

With the development of wireless communication, the automatic modulation recognition technology of communicational signals becomes an important theme. In this paper, based on multivariate statistical principal component analysis, we select characteristics of the signal, and use radio monitoring equipment mined measurement data to do some processing and analysis, which provided technical support to automatic modulation recognition of the radio signal.

You might also be interested in these eBooks

Measuring Technology and Mechatronics Automation IV

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 128-129)

Pages:

1269-1272

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.128-129.1269

Citation:

Cite this paper

Online since:

October 2011

Authors:

Guang Hui Li, Zheng Pei, Ran Chen, Da Li Hu

Keywords:

Feature Selection, Modulation Recognition, Principal Component Analysis (PCA), SAS

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Nandi A K , Azzouz E E in: Recognition of analogue modulations , Signal Process , 1995, 46: (2): 211-222.

Google Scholar

[2] Azzouz E E, Nandi A Kin: Automatic identification of digital modulations, Signal Processing, 1995 47: (1): 55-69.

DOI: 10.1016/0165-1684(95)00099-2

Google Scholar

[3] Nandi A K, Azzouz E E in: Algorithms for automatic modulation recogntion of communication signals, Communications, IEEE Transactions on , 1998, 46(4): 431-436.

DOI: 10.1109/26.664294

Google Scholar

[4] Li Jingjing, in: The application of Hilbert transform in signal demodulation. [J] Journal of The PLA Information Engineering University. 2002. 12 . 3(4): 29-31.

Google Scholar

[5] Chen Huaixin, in: The signal modulation recognition based on statistical characteristics' principal component analysis. [J] Journal of University of Electronic Science and Technology of China 2004. 6 33(3): 231-236.

Google Scholar

[6] Yao yafeng, in: The communication signals modulation recognition identification technique. [J] Communications Technology 2003. 6 41-50.

Google Scholar

[7] Li Jingjing, in: The application of Hilbert transform in signal demodulation. [J] Journal of The PLA Information Engineering University. 2002. 12 . 3(4): 29-31.

Google Scholar

[8] Andrzej Czyzewski , in: Automatic identification of sound source position employing neural networks and rough sets , Pattern Recognition Letters 24 (2003) 921–933.

DOI: 10.1016/s0167-8655(02)00204-0

Google Scholar