NDLI: A method of life signal identification based on BP neural network

Content Provider	IEEE Xplore Digital Library
Author	Hongxia Guo
Copyright Year	2011
Description	Author affiliation: Preps Dept. of Engineering College of the Chinese, People's Armed Police Force, Xian, China (Hongxia Guo)
Abstract	Ultra wide band (UWB) life detector can penetrate walls and ruins to detect whether there is a sign of life on the rear. This device will play an important role in anti-terrorism and disaster relief. But because the life signal is low frequency, quasi-periodic, non-stationary and low signal to noise ratio (SNR) and so on, such features restrict the accuracy of identifying life signals. According to the characteristics of life signals, back propagation (BP) neural network is chosen as the life signal recognition method, and the proper network structure is designed with appropriate network parameters selected. Simulation results show that, using BP neural network method can greatly improve the life signal identification accuracy; it is proved to be an effective method in the practical project.
Starting Page	22
Ending Page	25
File Size	448523
Page Count	4
File Format	PDF
ISBN	9781424493043
e-ISBN	9781424493067
DOI	10.1109/CISP.2011.6099970
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Accuracy BP neural network Detectors life signal identification simulation in MATLAB Biological neural networks Frequency domain analysis Signal to noise ratio life detector
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

The Research of Alphabet Identification Based on Genetic BP Neural Network

Transformer failure diagnosis based on BP neural network

Adaptive BP neural network (ABPNN) based PN code acquisition system via recursive accumulator

Blind Multi-user Detection Based on BP Neural Network

A deep neural network for time-domain signal reconstruction

Efficiency Evaluation Method of Simulation System Based on BP Neural Network

Seismic denoising based on modified BP neural network

Compensation method of PSD's background light based on improved BP neural network

A robust real-time pitch detector based on neural networks

A method of life signal identification based on BP neural network

Similar Documents

The Research of Alphabet Identification Based on Genetic BP Neural Network

Transformer failure diagnosis based on BP neural network

Adaptive BP neural network (ABPNN) based PN code acquisition system via recursive accumulator

Blind Multi-user Detection Based on BP Neural Network

A deep neural network for time-domain signal reconstruction

Efficiency Evaluation Method of Simulation System Based on BP Neural Network

Seismic denoising based on modified BP neural network

Compensation method of PSD's background light based on improved BP neural network

A robust real-time pitch detector based on neural networks

A method of life signal identification based on BP neural network