NDLI: Feature Bispectra Based Real Time FM Signal Recognition Using Adaptive Incremental Learning Feedforward Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Yuchun, Huang Zailu, Huang Benxiong, Huang Shuhua, Xu
Copyright Year	2007
Description	Author affiliation: Dept. of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China. Tel: +86-27-63180910, E-mail: supermiracle@163.com (Yuchun, Huang; Zailu, Huang; Benxiong, Huang; Shuhua, Xu)
Abstract	On-line real time automatic communication signal¿ Frequency Modulated (FM) signal recognition has been a hot topic recently, which focuses on finding the characteristic feature in the noisy signal observations comprehensively identifying the the same or different version of transmitting devices with approximate performance parameters in modern electronic warfare. Direct use of Higher Order Statistics (HOS) becomes unavailable for this on-line application because of its huge computation time and memory space especially in the case of high frequency FM signal. This paper presents a novel view to improve the HOS analysis efficiency greatly by sub-sampling and its ability to detect the nonlinear parasitic amplitude modulation spontaneous frequency coupling while preserving the noise-contaminated feature and eliminating the random Gaussian noise. FM signal-related feature bispectra selection easily and significantly translates the 2-D feature matching pattern to a 1-D one applicable for an adaptive incremental learning Single-hidden Layer Feedforward Network (SLFN), which has been shown to be extremely fast with good generalization performance. Apart from the noise-to-signal level estimation as the expected learning accuracy, no other control parameters have to be manually chosen for this simple SLFN with adaptively incremental random hidden nodes one-by-one or chunk-by-chunk of fixed or varying chunk size. Simulation experiments show that this novel feature bispectra and adaptive incremental multi-class learning network outperform AIB, SB and BP, RBF in terms of computation time and recognition rate for on-line steady FM signal recognition.
Starting Page	1
Ending Page	7
File Size	4569412
Page Count	7
File Format	PDF
ISBN	9781424415120
DOI	10.1109/MILCOM.2007.4455091
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Feedforward neural networks Frequency modulation Signal processing Gaussian noise Noise level Character recognition Electronic warfare Higher order statistics Military computing Adaptive Incremental Learning Sub-sampling Feature Bispectra single hidden layer feedforward network (SLFN)
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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