Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96727
Title: Time-frequency peak filtering for the recognition of communication signals
Authors: Zhang, Haijian
Bi, Guoan
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Abstract: Most existing classification methods cannot work in low signal-to-noise ratio (SNR) environments. This limitation motivates the signal filtering before the classification process. In this paper, a general framework that links the time-frequency peak filtering (TFPF) and traditional feature-based signal classification is explored. As the name suggests, TFPF is a filtering approach to encode the received signal as the instantaneous frequency (IF) of an analytic signal, and then the filtered signal is obtained by estimating the peak in the time-frequency domain of the encoded signal. The proposed framework is tested on the recognition of some communication signals. Numerical results demonstrate the effectiveness of this classification scheme for heavily noise corrupted signals. The TFPF based signal classification method exhibits a much better classification performance than the cases where the filtering process is not used.
URI: https://hdl.handle.net/10356/96727
http://hdl.handle.net/10220/13117
DOI: 10.1109/MSNA.2012.6324507
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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