• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.12-18
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• 2001

SAR radar and FLIR images, which are taken from sensors on aircrafts or satellites, are compressed prior to transmission to facilitate rapid transfer through the limited bandwidth channels. In this case, it is important that it achieves compression ratio as high as possible as well as high target detection rate. In this paper a joint ATR-compression system based on the subband coding and VQ is proposed, which utilizes the encoder as a predictor or classifier for target detection. Simulation result shows that the proposed system achieves a relatively high level of target detection performance as well as a high compression ratio over 200:1.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.7
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• pp.844-850
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• 2016

This study pertains to the extraction of the road noise component of signals from a vehicle's interior noise via the traditional frequency domain and time domain system identification methods. For road noise extraction based on the frequency domain system identification method, the appropriate matrix inversion strategy is investigated and causal and non-causal impulse response filters are compared. Furthermore, appropriate data lengths for the frequency domain system identification method are investigated. In addition to the traditional road noise extraction methods based on frequency domain system identification, a new approach to extract road noise via the time domain system identification method based on a parametric input-output model is proposed and investigated in the present study. In this approach, instead of constructing a higher order model for the full-band road noise, input and output signals are processed in the subband domain and lower order parametric models optimal to each subband are determined. These parametric models are used to extract road noises in each subband; the full band road noise is then reconstructed from the subband road noises. This study shows that both the methods in the frequency domain and the time domain successfully extract the road noise from the vehicle's interior noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.1 s.106
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• pp.27-33
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• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.161-164
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• 2000

본 논문에서 제안한 동시통화 검출기는 기존의 전대역에서 이루어지던 상호상관계수를 이용한 동시통화 검출기의 검출성능을 향상시키기 위하여 웨이브릿변환된 각각의 서브밴드 내에서 동시통화 및 반향경로를 구별하여 효율적으로 검출할 수 있도록 구성하였다. 서브밴드 동시통화 검출기 사용으로 동시통화 시에 발생하는 적응필터의 계수 발산을 막음으로써 시스템의 안정성을 높이고, 근단화자 신호가 원단화자에게 더 유쾌하게 들릴 수 있게 함으로써 원활한 통화환경을 제공할 수 있도록 구현하였다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.313-316
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• 2000

Wavelet transform has specific properties for image coding. The property used at this Paper is clustering of significant coefficients across subband. These coefficients are classified in significant coefficient and insignificant coefficient on a threshold value, and symbolized EZW decreases symbol-position information using zero-trees, but threshold value fall for raising resolution, then coding cost of significant coefficients is expensive. To avoid this fact, this paper uses quad-tree representing coefficient-position information. a magnitude of significant coefficient is represented on matrix used at EZW. the proposed algorithm is hoped for raising a coding cost.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.1-6
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• 2003

It is difficult to detect and to track the moving targets like tanks and diesel vehicles due to the variety of terrain and moving of targets. It is possible to be happened the aliasing conditions as the difficulty of antenna deployment in the complex environment like the battle fields. In this paper, we study the problem of detecting and tracking of moving targets which are emitting wideband signals under severe spatial aliasing conditions because of the sparse arrays. We developed a direction of arrival(DOA) estimation algorithm based on subband MUSIC(Multiple Signal Classification) method which produces high-resolution estimation. In this algorithm, the true bearings are invariant regardless of changes of frequency bands while the aliased false bearings vary. As a result, the proposed algorithm overcomes the aliasing effects and improves the localization performance in sparse passive arrays.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.706-715
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• 2004

In this paper, to decide the watermark embedding positions and embed the watermark we use the subband tee structure which is presented in the wavelet domain and the edge information in the spatial domain. The significant frequency region is estimated by the subband searching from the higher frequency subband to the lower frequency subband. LH1 subband which has the higher frequency in tree structure of the wavelet domain is divided into 4${\times}$4 submatrices, and the threshold which is used in the watermark embedding is obtained by the blockmatrix which is consists by the average of 4${\times}$4 submatrices. Also the watermark embedding position, Keymap is generated by the blockmatrix for the energy distribution in the frequency domain and the edge information in the spatial domain. The watermark is embedded into the wavelet coefficients using the Keymap and the random sequence generated by LFSR(Linear feedback shift register). Finally after the inverse wavelet transform the watermark embedded image is obtained. the proposed watermarking algorithm showed PSNR over 2㏈ and had the higher results from 2％ to 8％ in the comparison with the previous research for the attack such as the JPEG compression and the general image processing just like blurring, sharpening and gaussian noise.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.119-128
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• 2017

In this paper, the wideband direction finding algorithm and system design method for short duration signal such as frequency hopping or burst signal is presented. The polyphase filterbank that it is possible for the near perfect reconstruction was used as a pre-processing and in each subband power measurement was performed to determine whether the presence of a signal and finally general direction finding algorithm was performed. In addition, various experiments was performed using Matlab Simulink and collected data from wideband receiver to verification of the proposed algorithm.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.16-24
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• 2009

In this paper, we propose a new noise cancellation system for the NDIR based optical analyzer, that can measure various environmental air-pollution materials (CO, $SO_2$, NOx, etc.) in real-time. The sensed signals are contaminated by the different noise sources that measurement noise with high frequencies and the drift noise with the low frequencies. They can be eliminated by a pre-processing that considering their time-domian properties and by a post-processing that using sub-power ratios in subband structure. In the proposed method, the ore and pose-processing for noise cancelling are useful for hardware implementation of the NDIR based optical analyzer with a precision measuring.