A Novel Demodulation System Based on Continuous Wavelet Transform
Considering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonline...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/513849 |
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doaj-c8e8ca07b9954a2f8098b94c9f007e882020-11-24T21:28:19ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/513849513849A Novel Demodulation System Based on Continuous Wavelet TransformLanting Fang0Lenan Wu1Yudong Zhang2School of Information Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Computer Science and Technology, Nanjing Normal University, Nanjing 210023, ChinaConsidering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonlinear demodulation system based on image processing and pattern classification is proposed. To evaluate the performance of the adaptive wavelet and compare the performance of the proposed system with the existing systems, a series of comprehensive simulation experiments is conducted under the environment of uniform white noise, colored noise, and additive white Gaussian noise channel, respectively. Simulation results of different wavelets show that the system using adaptive wavelet has lower bit error rate (BER). Moreover, simulation results of several systems show that the BER of the proposed system is the lowest among all systems, such as amplitude detection, integral detection, and some continuous wavelet transform systems (specific scales and times and maximum lines). In a word, the adaptive wavelet construction proposed in this paper yields superior performances compared with the manual selection, and the proposed system has better performances than the existing systems. Index terms are signal demodulation, adaptive wavelet, continuous wavelet transform, and BER.http://dx.doi.org/10.1155/2015/513849 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lanting Fang Lenan Wu Yudong Zhang |
spellingShingle |
Lanting Fang Lenan Wu Yudong Zhang A Novel Demodulation System Based on Continuous Wavelet Transform Mathematical Problems in Engineering |
author_facet |
Lanting Fang Lenan Wu Yudong Zhang |
author_sort |
Lanting Fang |
title |
A Novel Demodulation System Based on Continuous Wavelet Transform |
title_short |
A Novel Demodulation System Based on Continuous Wavelet Transform |
title_full |
A Novel Demodulation System Based on Continuous Wavelet Transform |
title_fullStr |
A Novel Demodulation System Based on Continuous Wavelet Transform |
title_full_unstemmed |
A Novel Demodulation System Based on Continuous Wavelet Transform |
title_sort |
novel demodulation system based on continuous wavelet transform |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2015-01-01 |
description |
Considering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonlinear demodulation system based on image processing and pattern classification is proposed. To evaluate the performance of the adaptive wavelet and compare the performance of the proposed system with the existing systems, a series of comprehensive simulation experiments is conducted under the environment of uniform white noise, colored noise, and additive white Gaussian noise channel, respectively. Simulation results of different wavelets show that the system using adaptive wavelet has lower bit error rate (BER). Moreover, simulation results of several systems show that the BER of the proposed system is the lowest among all systems, such as amplitude detection, integral detection, and some continuous wavelet transform systems (specific scales and times and maximum lines). In a word, the adaptive wavelet construction proposed in this paper yields superior performances compared with the manual selection, and the proposed system has better performances than the existing systems.
Index terms are signal demodulation, adaptive wavelet, continuous wavelet transform, and BER. |
url |
http://dx.doi.org/10.1155/2015/513849 |
work_keys_str_mv |
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