• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.967-970
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• 2014

An efficient peak detection algorithm in magnitude spectrum is proposed to distinguish the M-frequency shift keying(FSK) signals from other digitally modulated signal. In addition, recognition of the modulation order estimation of FSK signals is also studied based on the fact that the magnitude spectrum of FSK signals reveals the number of peaks equal to the modulation order. When no a priori information about the signals, we utilize the histogram of the magnitude spectrum to determine the threshold which is important factor in peak detection algorithm. The simulation results show high probability of classification under 500 symbols and signal-to-noise ratio(SNR) higher than 4dB.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.31-36
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• 2012

In this paper, we proposed spectrum sensing using cooperative relay to solve problem of sensing performance degradation due to CPE (Customer-Premises equipments) which causes low SNR (signal-to-noise ratio) problem. In cooperative communication system, AF (amplify-and-forward) and DF (decoded-and-forward) is widely used for relay mechanism. Also, it is expected that cooperative relay scheme guarantees the high sensing performance by its diversity gain. Based on these backgrounds, in this paper, we apply to cooperative relay scheme to the CR (Cognitive Radio) system, and simulation results show comparison of the sensing performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.986-994
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• 2005

This Paper proposes the likelihood-based nonlinear dimension reduction method of the speech feature parameters in order to construct the voice activity detecter adaptable in noisy environment. The proposed method uses the nonlinear values of the Gaussian probability density function with the new parameters for the speec/nonspeech class. We adapted Likelihood Ratio Test to find speech part and compared its performance with that of Linear Discriminant Analysis technique. In experiments we found that the proposed method has the similar results to that of Gaussian Mixture Models.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.27-35
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• 1999

In this paper, we propose an error detection scheme of phase offsets for binary sequences including PN (Pseudo Noise) sequences based on the number theoretical approach. It is important to know phase offsets of spreading sequences in the CDMA (Code Division Multiple Access) mobile communication systems because phase offsets of the same spreading sequence are used to achieve the acquisition and are used to distinguish each base station. When the period of the sequence is not very long, the relative phase offset between the sequence and its shifted replica can be found by comparing them, but as the period of the sequence increases it becomes difficult to find the phase offset. The error detection failure probability of the proposed method is derived, and it is confirmed by the simulation results. We also discuss the circuit realization of the proposed method and show it can be easily implemented.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.285-289
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• 2009

In this paper, we propose a novel double-talk detection (DTD) technique based on soft decision in the frequency domain. In the proposed method, global near-end speech presence probability (GNSPP) considering the statistical model assumption and voice activity detection (VAD) decision of the near-end and far-end signal are applied to the DTD algorithm in the frequency domain instead of the traditional hard decision scheme using cross-correlation coefficients. The performance of the proposed algorithm is evaluated by the objective test under various environments, and yields better results compared with the conventional scheme.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.56-62
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• 2001

In this paper, we adopt a missing data theory to speech recognition. It can be used in order to maintain high performance of speech recognizer when the missing data occurs. In general, hidden Markov model (HMM) is used as a stochastic classifier for speech recognition task. Acoustic events are represented by continuous probability density function in continuous density HMM(CDHMM). The missing data theory has an advantage that can be easily applicable to this CDHMM. A marginalization method is used for processing missing data because it has small complexity and is easy to apply to automatic speech recognition (ASR). Also, a spectral subtraction is used for detecting missing data. If the difference between the energy of speech and that of background noise is below given threshold value, we determine that missing has occurred. We propose a new method that examines the reliability of detected missing data using voicing probability. The voicing probability is used to find voiced frames. It is used to process the missing data in voiced region that has more redundant information than consonants. The experimental results showed that our method improves performance than baseline system that uses spectral subtraction method only. In 452 words isolated word recognition experiment, the proposed method using the voicing probability reduced the average word error rate by 12％ in a typical noise situation.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.150-156
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• 2011

In this paper, infrared thermography measurement technique has been used to develop standard measurement technique for nondestructive testing of composite materials which is widely used in aerospace industries. To increase the defect detection rate, the related experiment used the lock-in IR-thermographiy method. Therefore it is of considerable interest in the field of non-destructive testing for fast discontinuity detection by using ultrasonic lock-in infrared thermography. The result also shows that as the investigation period of light source is lengthened according to the thickness of specimen, the possibility of detecting defects gets higher as well. However, the reason why the result values were not favorable when less than 50 mHz of light source was provided is because it was difficult to detect defects as the defect parts became a state of thermal equilibrium in general when thermal diffusivity affects the entire materials.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.1-8
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• 2016

We propose an adaptive histogram stretching algorithm for application to a car's personal recorder. The algorithm was used for pre-processing to detect the license plate region in an image from a personal recorder. The algorithm employs a Probability Density Function (PDF) and Cumulative Distribution Function (CDF) to analyze the distribution diagram of the images. These two functions are calculated using an image obtained by sampling at a certain pixel interval. The images were subjected to different levels of stretching, and experiments were done on the images to extract their characteristics. The results show that the proposed algorithm provides less deterioration than conventional algorithms. Moreover, contrast is enhanced according to the characteristics of the image. The algorithm could provide better performance than existing algorithms in applications for detecting search regions for license plates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.536-542
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• 2011

For efficient utilization of spectrum resources in TV white space after DTV transition, FCC allowed usage of the spectrum for CR system. The CR system is required to cognize channel usage state for utilizing the unused spectrum in TV white space which coexists various primary and secondary systems. In the meantime, as a demand for high throughput communication had been increased recently, CR systems also consider to adopt channel bonding technology, thus spectrum sensing for channel bonded system is essentially required. In this paper, we propose a novel spectrum sensing algorithm for channel bonding system using a single channel receiver. For IEEE 802.l1af signal, the proposed algorithm provide detection probability of 90% with false alarm probability 10% at SNR -18dB for single channel system and at SNR -7dB for 8 channel bonded system, respectively. Utilizing the proposed scheme, we can detect channel bonded signal using only a single receiver, therefore system overhead for spectrum sensing can be reduced significantly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7A
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• pp.733-742
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• 2008

In 3GPP LTE downlink system, initial cell search is essential for mobile station to connect to base station. In order to obtain information of the base station, the mobile station detects frame timing, frequency offset, and cell identification using primary synchronization channel(PSC) and secondary synchronization channel(SSC), which are defined in downlink OFDMA specification. In this paper, we analyze various detection algorithms in practical environment of inter-cell-interference, frequency offset, and multi-path fading channel and propose the optimal algorithm. Simulation results show that partial correlation method (for PSC acquisition) and interference cancellation method (for SSC detection) are the most superior algorithms among the applicable algorithms. Employ these two algorithms for receiver design, initial cell search is performed with 99% probability within 70ms in the channel environment considered.