Commenced in January 2007
Paper Count: 30455
Development of Intelligent Time/Frequency Based Signal Detection Algorithm for Intrusion Detection System
Abstract:For the past couple of decades Weak signal detection is of crucial importance in various engineering and scientific applications. It finds its application in areas like Wireless communication, Radars, Aerospace engineering, Control systems and many of those. Usually weak signal detection requires phase sensitive detector and demodulation module to detect and analyze the signal. This article gives you a preamble to intrusion detection system which can effectively detect a weak signal from a multiplexed signal. By carefully inspecting and analyzing the respective signal, this system can successfully indicate any peripheral intrusion. Intrusion detection system (IDS) is a comprehensive and easy approach towards detecting and analyzing any signal that is weakened and garbled due to low signal to noise ratio (SNR). This approach finds significant importance in applications like peripheral security systems.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070353Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2181
 M. Zhang and W. Huang, "Design and implementation of a weak signal detecting system based on LabWindows," in Wireless and Mobile Communications, 2009. ICWMC -09. Fifth International Conference on, Aug. 2009, pp. 245 -250.
 X. Liu and X. Feng, "Research on weak signal detection for downhole acoustic telemetry system," in Image and Signal Processing (CISP), 2010 3rd International Congress on, vol. 9, Oct. 2010, pp. 4432 -4435.
 E. Causevic, R. Morley, M. Wickerhauser, and A. Jacquin, "Fast wavelet estimation of weak biosignals," Biomedical Engineering, IEEE Transactions on, vol. 52, no. 6, pp. 1021 -1032, Jun. 2005.
 Z. Qin, L. Chen, and X. Bao, "Wavelet denoising method for improving detection performance of distributed vibration sensor," Photonics Technology Letters, IEEE, vol. 24, no. 7, pp. 542 -544, Apr. 2012.
 L. Gao, S. Liu, Z. Yin, L. Zhang, L. Chen, and X. Chen, "Fiber-Optic vibration sensor based on beat frequency and Frequency-Modulation demodulation techniques," Photonics Technology Letters, IEEE, vol. 23, no. 1, pp. 18 -20, Jan. 2011.
 H. Hoidalen and M. Runde, "Continuous monitoring of circuit breakersusing vibration analysis," Power Delivery, IEEE Transactions on, vol. 20, no. 4, pp. 2458 - 2465, Oct. 2005.
 P. Zhou, M. Lowery, R. Weir, and T. Kuiken, "Elimination of ECG artifacts from myoelectric prosthesis control signals developed by targeted muscle reinnervation," in Engineering in Medicine and Biology Society,2005. IEEE-EMBS 2005. 27th Annual International Conference of the,Jan. 2005, pp. 5276 -5279.
 Y. Cao, C. Chen, and Y. Hu, "Application of independent component analysis to ECG cancellation in surface electromyography measurement," Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, vol. 22, no. 4, pp.686-689, Aug 2005, PMID: 16156250.
 J. Allen, "Applications of the short time fourier transform to speech processing and spectral analysis," in Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP -82., vol. 7, May1982, pp. 1012 - 1015.
 V. Chen and S. Qian, "Joint time-frequency transform for radar rangedoppler imaging," IEEE Transactions on Aerospace and Electronic Systems, vol. 34, no. 2, pp. 486 -499, Apr. 1998.
 C. Yan and Z. Rubo, "The application of short time fractional fourier transform in processing underwater multi-frequency LFM signal," in Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC), 2011, vol. 2, Jul. 2011, pp. 1472 -1475.
 H. Kwok and D. Jones, "Improved instantaneous frequency estimation using an adaptive short-time fourier transform," IEEE Transactions on Signal Processing, vol. 48, no. 10, pp. 2964 -2972, Oct. 2000.