• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.425-430
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• 2017

This paper presents a novel method for identification of FSK modulated radar signal. Three features which measure the number of frequency tones, the regularity of the frequency shifting, and the diversity of power spectrum of detected radar signal, are introduced. A Two-step combined maximum likelihood classifier was used to identify the details of the detected FSK signal; the modulation order and the use of Costas code. We attempted to divide FSK signal into binary FSK, ternary FSK, 8-ary FSK, and FSK with Costas code of length 7. The simulation results indicated that the proposed methods achieves an averaged identification accuracy was 99.93% at a signal-to-noise of 0 dB.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.494-502
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• 2007

Ubiquitous location based services (u-LBS) will be interested to an important services. They can easily recognize object position at anytime, anywhere. At present, many researchers are making a study of the position recognition and tracking. This paper consists of postion recognition and user identification system. The position recognition is based on location under services (LBS) using a signal strength map, a database is previously made use of empirical measured received signal strength indicator (RSSI). The user identification system automatically controls instruments which is located in home. Moreover users are able to measures body signal freely. We implemented the multi-hop routing method using the Star-Mesh networks. Also, we use the sensor devices which are satisfied with the IEEE 802.15.4 specification. The used devices are the Nano-24 modules in Octacomm Co. Ltd. A RSSI is very important factor in position recognition analysis. It makes use of the way that decides position recognition and user identification in narrow indoor space. In experiments, we can analyze properties of the RSSI, draw the parameter about position recognition. The experimental result is that RSSI value is attenuated according to increasing distances. It also derives property of the radio frequency (RF) signal. Moreover, we express the monitoring program using the Microsoft C#. Finally, the proposed methods are expected to protect a sudden death and an accident in home.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4808-4824
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• 2016

Signal individual reconnaissance and identification is an extremely important research topic in non-cooperative domains such as electronic countermeasures and intelligence reconnaissance. Facing the characteristics of the complexity and changeability of current communication environment, how to realize radiation source signal individual identification under the low SNR conditions is an emphasis of research. A novel emitter individual identification method combined bi-spectrum analysis with wavelet feature is presented in this paper. It makes a feature fusion of bi-spectrum slice characteristics and energy variance characteristics of the secondary wavelet transform coefficient to identify MFSK signals under the low SNR (signal-to-noise ratios) environment. Theoretical analyses and computer simulation results show that the proposed algorithm has good recognition performance with the ability to suppress noise and interference, and reaches the recognition rate of more than 90% when the SNR is -6dB.

• Structural Monitoring and Maintenance
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• v.11 no.3
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• pp.203-217
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• 2024

Electro-mechanical impedance (EMI) technique is a low-cost structural damage detection method. It reflects structural damage through the change in admittance signal which contains the structural mechanical impedance information. The ambient temperature greatly affects the admittance signal, which hides the changes caused by structural damage and reduces the accuracy of damage identification. This study introduces a convolutional neural network to compensate for the temperature effect. The proposed method uses a framework that consists of a feature extraction network and a decoding network, and the original admittance signal with temperature information is used as the input. The output admittance signal is eliminated from the temperature effect, improving damage identification robustness. The admittance data simulated by the finite element model of the spatial grid structure is used to verify the effectiveness of the proposed method. The results show that the proposed method has advantages in identification accuracy compared with the damage index minimization method and the principal component analysis method.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.83-91
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• 1993

A ghost cancelling method using the multiplicationless adaptive multipath channel identification is proposed. The IIR filter and the LMS algorithm are used for ghost cancelling. The coefficients of IIR filter are obtained by multipath channel identification. The LMS algorithm which is simple relatively is used as the adaptive algorithm. An MPS is selected as the reference signal and it is used as the input of the adaptive algorithm for the multipath channel identification. If an MPS is not exist, the horizontal syne, and color burst signal can be used as the reference signal. Improving of accuracy of the ghost cancelling in the presence of the phase variation in the multipath channel, a complex processing are also performed.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.65-73
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• 1989

In this paper, we propose a text-independent speaker identification algorithm based on VQ(vector quantization) and vowel classification, and its performance is studied and compared with that of a conventional speaker identification algorithm using VQ. The proposed speaker identification algorithm is composed of three processes: vowel segmentation, vowel recognition and average distortion calculation. The vowel segmentation is performed automatlcally using RMS energy, BTR(Back-to-Total cavity volume Ratio)and SFBR(Signed Front-to-Back maximum area Ratio) extracted from input speech signal. If the Input speech signal Is noisy, particularity when the SNR is around 20dB, the proposed speaker identification algorithm performs better than the reference speaker identification algorithm when the correct vowel segmentation is done. The same result is obtained when we use the noisy telephone speech signal as an input, too.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.142-148
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• 2016

Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.

• Journal of Sensor Science and Technology
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• v.26 no.3
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• pp.192-198
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• 2017

In this paper, we newly developed a passive transponder for visible light identification (VLID) using ultrasonic wave. The solar cell in the transponder receives the reader light and generates current for supplying power to the transponder circuit. At the same time the solar cell detects the interrogating signal in the visible light from the reader. The transponder recognizes the interrogating signal and generates the responding signal using ultrasonic wave. In experiments, we used 40 kHz ultrasonic wave for the responding signal from the transponder. The maximum read distance was about 3.4 m when the transponder was exposed to the reader light of 24W LED array.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.75-80
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• 1999

Signal separation and transmission are essential for automatic breeding management of domestic animals. Electronic identification system could transmit the signal of an individual within a defined range to a personal computer by an electromagnetic signal recognition method. Signals for individual recognition were originated by controlling 12 tri-state pins of IC(PT2262) in a transmitter. PT 2262 can generate 4,096 codes. These encoded signals were modulated and transmitted with wireless lines from the transmitter. Then they were demodulated in a receiver, and the signals were transmitted to the micro-processor through an interface and were identified in a PC.