Intrusion recognition method based on echo state network for optical fiber perimeter security systems

Wang, Ningning; Fang, Nian; Wang, Lutang

doi:10.1016/j.optcom.2019.06.058

Cited by 24 publications

(19 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Concerning an optical packet switching network, a correct recognition of the optical packet header is crucial, which can ensure that the data are transmitted to a correct route [ 27 , 28 ]. If the multiple-input multiple-output optoelectronic RC system can successfully realize the simultaneous recognition of the multiple-route optical packet headers, it can be employed as an important equipment for the optical network switching nodes.…”

Section: Simulation Results Of Signal Recognitionsmentioning

confidence: 99%

A Multiple-Input Multiple-Output Reservoir Computing System Subject to Optoelectronic Feedbacks and Mutual Coupling

Bao

Zhao

Yin

2020

Entropy

View full text Add to dashboard Cite

In this paper, a multiple-input multiple-output reservoir computing (RC) system is proposed, which is composed of multiple nonlinear nodes (Mach–Zehnder modulators) and multiple mutual-coupling loops of optoelectronic delay lines. Each input signal is added into every mutual-coupling loop to implement the simultaneous recognition of multiple route signals, which results in the signal processing speed improving and the number of routes increasing. As an example, the four-route input and four-route output RC is simultaneously realized by numerical simulations. The results show that this type of RC system can successfully recognize the four-route optical packet headers with 3-bit, 8-bit, 16-bit, and 32-bit, and four-route independent digital speeches. When the white noise is added to the signals such that the signal-to-noise ratio (SNR) of the optical packet headers and the digital speeches are 35 dB and 20 dB respectively, the normalized root mean square errors (NRMSEs) of the signal recognition are all close to 0.1. The word error rates (WERs) of the optical packet header recognition are 0%. The WER of the digital speech recognition is 1.6%. The eight-route input and eight-route output RC is also numerically simulated. The recognition of the eight-route 3-bit optical packet headers is implemented. The parallel processing of multiple-route signals and the high recognition accuracy are implemented by this proposed system.

show abstract

Section: Simulation Results Of Signal Recognitionsmentioning

confidence: 99%

A Multiple-Input Multiple-Output Reservoir Computing System Subject to Optoelectronic Feedbacks and Mutual Coupling

Bao

Zhao

Yin

2020

Entropy

View full text Add to dashboard Cite

show abstract

“…With reference to the above experimental setup, according to this method, the characteristic of fiber vibration signal was extracted, obtaining the characteristics of intrusion signals such as shaking protection nets, knocking protection nets, and over-protection fences, and obtaining their respective feature sets after condensing. The method of reference from [4], the method of reference from [5], and the proposed method were used to identify and identify the intrusion signals. The recognition results were obtained by identifying and comparing the features.…”

Section: Comparison Of Intrusion Signal Recognition Accuracymentioning

confidence: 99%

“…Dividing the correct recognition of each category by the number of test signals and calculating the accuracy of their identification, we received the results shown in Table 1. According to the data in Table 1, the average recognition accuracy rate of intrusion signal of reference [4] method is 79.9%, that of reference [5] method is 76.6%, and that of the proposed method is as high as 94.4%. It can be seen that the recognition accuracy of intrusion signals such as the shaking protection net, striking protection net, and crossing the protection fence of the proposed method are higher than those of the reference [4] method and the reference [5] method.…”

Section: Comparison Of Intrusion Signal Recognition Accuracymentioning

confidence: 99%

“…In [4], an intrusion signal recognition method based on echo state network is proposed. Sagnac interferometer was used to simulate the sensing optical fiber to obtain various event signals.…”

Section: Introductionmentioning

confidence: 99%

“…In this part, the amplitude of the intrusion vibration signal was measured by the experimental environment, and the noise problem was also considered. The method in this paper was compared with the method in [4,5], and the accuracy of intrusion signal recognition, the iteration loss value of training set, the identification efficiency of intrusion events, and the response sensitivity of intrusion events were compared and analyzed. The results showed that the accuracy and efficiency of this method were high, the false alarm rate of the intrusion signal was greatly reduced, and the overall stability of the recognition system was improved.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pattern Recognition of Grating Perimeter Intrusion Behavior in Deep Learning Method

Hua

2021

Symmetry

View full text Add to dashboard Cite

An intrusion behavior recognition method based on deep learning is proposed in this paper in order to improve the recognition accuracy of raster perimeter intrusion behavior. The Mach–Zehnder fiber optic interferometer was used to collect the external vibration signal sensing unit, capture the external vibration signal, use the cross-correlation characteristic method to obtain the minimum frame length of the fiber vibration signal, and preprocess the intrusion signal according to the signal strength. The intrusion signals were superimposed and several sections of signals were intercepted by fixed window length; the spectrum information is obtained by Fourier transform of the intercepted stationary signals. The convolution neural network was introduced into the pattern recognition of the intrusion signals in the optical fiber perimeter defense zone, and the different characteristics of the intrusion signals were extracted, so as to realize the accurate identification of different intrusion signals. Experimental results showed that this method was highly sensitive to intrusion events, could effectively reduce the false alarm rate of intrusion signals, and could improve the accuracy and efficiency of intrusion signal recognition.

show abstract

A comprehensive bibliometric analysis of signal processing and pattern recognition based on distributed optical fiber

Zhu

Yang

et al. 2023

Measurement

View full text Add to dashboard Cite

Intrusion recognition method based on echo state network for optical fiber perimeter security systems

Cited by 24 publications

References 21 publications

A Multiple-Input Multiple-Output Reservoir Computing System Subject to Optoelectronic Feedbacks and Mutual Coupling

A Multiple-Input Multiple-Output Reservoir Computing System Subject to Optoelectronic Feedbacks and Mutual Coupling

Pattern Recognition of Grating Perimeter Intrusion Behavior in Deep Learning Method

A comprehensive bibliometric analysis of signal processing and pattern recognition based on distributed optical fiber

Contact Info

Product

Resources

About