Study on fractal features of modulation signals
Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension extracted from received signals as features of classification. These features contain the characteristics of magnitude, frequency and phase of signals, a...
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Published in | Science China. Information sciences Vol. 44; no. 2; pp. 152 - 158 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Heidelberg
Springer Nature B.V
01.04.2001
Department of Automatization, Tsinghua University,%Department of Electronic Engineering, University of Electronic Science and Technology of China |
Subjects | |
Online Access | Get full text |
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Abstract | Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension extracted from received signals as features of classification. These features contain the characteristics of magnitude, frequency and phase of signals, and collect discriminatory information among various modulation modes. They are effective features in classification sense, and are insensitive to noises interfering. The theoretical analysis also proves the above conclusion. The classifier design is very simple based on such features. The simulation results show that the performances of signal classification are superior. |
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AbstractList | TN91; Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension extracted from received signals as features of classification. These features contain the characteristics of magnitude, frequency and phase of signals, and collect discriminatory information among various modulation modes. They are effective features in classification sense, and are insensitive to noises interfering. The theoretical analysis also proves the above conclusion. The classifier design is very simple based on such features. The simulation results show that the performances of signal classification are superior. Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension extracted from received signals as features of classification. These features contain the characteristics of magnitude, frequency and phase of signals, and collect discriminatory information among various modulation modes. They are effective features in classification sense, and are insensitive to noises interfering. The theoretical analysis also proves the above conclusion. The classifier design is very simple based on such features. The simulation results show that the performances of signal classification are superior. |
Author | Guo, Shuangbing Xiao, Xianci Lü, Tiejun |
AuthorAffiliation | Department of Automatization, Tsinghua University,%Department of Electronic Engineering, University of Electronic Science and Technology of China |
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Cites_doi | 10.1109/MILCOM.1995.483654 10.1016/S0165-1684(96)00165-X 10.1016/0165-1684(91)90012-8 |
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Copyright | Science in China Press 2001. Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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DOI | 10.1007/BF02713973 |
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References | A. K. Nandi (BF02713973_CR4) 1997; 56 Mingquan Lu (BF02713973_CR6) 1999; 16 Heping Xie (BF02713973_CR5) 1998 L. V. Dominguez (BF02713973_CR3) 1991; 22 K. C. Ho (BF02713973_CR2) 1995 K. Assaleh (BF02713973_CR1) 1992 |
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Snippet | Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension extracted... TN91; Based on fractal theory, the note presents a novel method of modulation signals classification that adopts box dimension and information dimension... |
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Title | Study on fractal features of modulation signals |
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