• 전기학회논문지
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• 제59권11호
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• pp.2108-2113
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• 2010

The Long Term Evolution (LTE) system is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the lattice-type pilot samples in the multipath fading channel environment. The estimation of the channel frequency response (CFR) makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time- and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. Any interpolation scheme could be adopted for this purpose. Depending on the requirements of the target system, we may choose a simple linear interpolation or a sophisticated one. For any choice of an interpolation scheme, these is a trade-off between estimation accuracy and numerical cost. For those wireless communication systems based on the OFDM and the preamble-type pilot structure, the DFT-based channel estimation and its variants have been successfully. Yet, it may not be suitable for the lattice-type pilot structure, since the pilot samples are not sufficient to provide an accurate estimate and it is known to be sensitive to the location as well as the length of the time-domain window. In this paper, we propose a simple interpolated based on the upsampling mechanism in the multirate signal processing. The proposed method provides an excellent alternative to the DFT-based methods in terms of numerical cost and accuracy. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification.

• 한국군사과학기술학회지
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• 제20권4호
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• pp.505-513
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• 2017

Cavitation is a phenomenon caused by vapour cavities that is produced in rapid pressure changes. When the cavitation happened, the sound pressure level of a underwater radiated noise is increased rapidly. As a result, it can increase the probability of the identification or classification of a our warship's acoustic signature by an enemy ship. However, there is a problem that it is hard to precisely detect the occurrence of a cavitation noise. Therefore, this paper presents recent improvements in terms of the cavitation noise measurement by using continuous wavelet transform and DEMON(Detection of Envelope Modulation on Noise) signal processing. Then, we present that the suggested scheme is more suitable for detecting the cavitation than existing algorithms.

• 디지털융복합연구
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• 제13권10호
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• pp.287-293
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• 2015

본 논문에서는 신호 처리 기술과 가중 퍼지소속함수 기반 신경망 (Neural Network with Weighted Fuzzy Membership Functions; NEWFM)을 이용하여 간질을 검출하는 방안을 제안하였다. 신호 처리 기술로는 웨이블릿 변환(Wavelet Transform), 점증적 증가 방법, 위상공간 재구성(Phase Space Reconstruction)을 이용하였다. 신호 처리 기술의 첫 번째 단계에서는 웨이블릿 변환을 이용하여 뇌파로부터 웨이블릿 계수를 추출하였다. 두 번째 단계에서는 점증적 증가 방법을 이용하여 웨이블릿 계수로부터 첨점(Peak)을 추출하였다. 세 번째 단계에서는 위상공간 재구성을 이용하여 추출된 첨점으로부터 3차원 다이어그램을 생성하였다. NEWFM의 입력으로 사용할 16개의 특징을 추출하기 위하여 유클리드 거리와 통계적 방법을 이용하였다. 이들 16개의 특징을 NEWFM의 입력으로 사용하여 97.5%, 100%, 95%의 정확도, 특이도, 민감도를 각각 구하였다.

• 한국멀티미디어학회논문지
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• 제8권1호
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• pp.46-55
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• 2005

본 논문에서는 소형 위협체를 조기에 탐지하여 위치를 알려주는 파노라믹 적외선 영상 경보 장치를 구현하였고, 경보 성능 향상을 위한 적외선 영상 향상 기법을 제안하였다. 구현 장치는 센서 헤드 유닛, 신호 처리 유닛 등으로 구성된다. 센서 헤드 유닛은 1차원 다중 배열 적외선 센서를 정속으로 고속 회전하여 360도의 넓은 시계 영역을 가지는 파노라믹 열영상을 획득한다. 신호 처리 유닛은 파노라믹 영상을 90도의 부영상으로 나누고, 각 부영역의 통계적 특성에 따라 적응적 평탄역값(adaptive plateau value)을 구한다 그리고 적응적 평탄역값으로 히스토그램을 변화시킴으로써 위협체을 두드러지게 하였으며, 실시간 처리를 위하여 DSP와 FPGA를 이용하여 장치를 구현하였다. 구현 시스템에 제안한 영상 향상 기법을 적용한 결과 기존 기법에 비해 오경보율이 낮음과 시각적으로 위협체의 식별이 용이함을 확인하였다.

• Smart Structures and Systems
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• 제10권3호
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• pp.253-269
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• 2012

A split spectrum processing (SSP) method is proposed to accurately determine the time-of-flight (ToF) of damage-scattered waves by comparing the instantaneous amplitude variation degree (IAVD) of a wave signal captured from a damage case with that from the benchmark. The fundamental symmetrical ($S_0$) mode in aluminum plates without and with a notch is assessed. The efficiency of the proposed SSP method and Hilbert transform in determining the ToF of damage-scattered $S_0$ mode is evaluated for damage identification when the wave signals are severely contaminated by noise. Broadband noise can overwhelm damage-scattered wave signals in the time domain, and the Hilbert transform is only competent for determining the ToF of damage-scattered $S_0$ mode in a noise-free condition. However, the calibrated IAVD of the captured wave signal is minimally affected by noise, and the proposed SSP method is capable of determining the ToF of damage-scattered $S_0$ mode accurately even though the captured wave signal is severely contaminated by broadband noise, leading to the successful identification of damage (within an error on the order of the damage size) using a triangulation algorithm.

• Journal of Communications and Networks
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• 제17권2호
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• pp.184-197
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• 2015

This paper builds on a recent method, chain routing with even energy consumption (CREEC), for designing a wireless sensor network with chain topology and for scheduling the communication to ensure even average energy consumption in the network. In here a new suboptimal design is proposed and compared with the CREEC design. The chain topology in CREEC is reconfigured after each group of n converge-casts with the goal of making the energy consumption along the new paths between the nodes in the chain as even as possible. The new method described in this paper designs a single near-optimal Hamiltonian circuit, used to obtain multiple chains having only the terminal nodes different at different converge-casts. The advantage of the new scheme is that for the whole life of the network most of the communication takes place between same pairs of nodes, therefore keeping topology reconfigurations at a minimum. The optimal scheduling of the communication between the network and base station in order to maximize network lifetime, given the chosen minimum length circuit, becomes a simple linear programming problem which needs to be solved only once, at the initialization stage. The maximum lifetime obtained when using any combination of chains is shown to be upper bounded by the solution of a suitable linear programming problem. The upper bounds show that the proposed method provides near-optimal solutions for several wireless sensor network parameter sets.

• 한국음향학회지
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• 제26권4호
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• pp.144-152
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• 2007

기존의 심음분류를 위한 연구들은 인공신경망을 이용하여 주로 이루어졌다. 그러나 심음신호의 통계적 특성을 분석 한 결과 HMM의 의한 신호모델링이 적합한 것으로 나타났다. 본 연구에서는 다양한 질병을 나타내는 심음신호를 HMM을 이용하여 모델링 하고 인식성능이 심음신호의 클러스터링에 따라서 많이 좌우되는 것을 알 수 있었다. 또한 실제 환경에서의 심음신호는 그 시작과 끝나는 시점이 정해지지 않은 연속신호이다. 따라서 HMM을 이용한 심음분류를 위해서는 연속적인 심음신호로부터 한 사이클의 분할된 심음을 추출할 필요성이 있다. 일반적으로 수동분할은 분할오류를 발생시키며 실시간 심음인식에 적합하지 않으므로 분할과정이 필요치 않는 ergodic형 HMM을 변형하여 사용할 것을 제안하였다. 그리고 제안된 HMM은 연속심음을 이용한 분류실험에서 매우 높은 성능을 보임을 알 수 있었다.

• Journal of applied mathematics & informatics
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• 제26권5_6호
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• pp.1149-1159
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• 2008

Blind source extraction (BSE) is a special class of blind source separation (BSS) methods, which only extracts one or a subset of the sources at a time. Based on the time delay of the desired signal, a simple but important extraction algorithm (simplified " BC algorithm")was presented by Barros and Cichocki. However, the performance of this method is not satisfying in some cases for which it only carries out the constrained minimization of the mean squared error. To overcome these drawbacks, ICA with reference (ICA-R) based approach, which considers the higher-order statistics of sources, is added as the second stage for further source extraction. Specifically, BC algorithm is exploited to roughly extract the desired signal. Then the extracted signal in the first stage, as the reference signal of ICA-R method, is further used to extract the desired sources as cleanly as possible. Simulations on synthetic data and real-world data show its validity and usefulness.

• ETRI Journal
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• 제41권3호
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• pp.316-325
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• 2019

Accurate suppressive jamming is a prominent problem faced by radar equipment. It is difficult to solve signal detection problems for extremely low signal to noise ratios using traditional signal processing methods. In this study, a joint sensing dictionary based compressed sensing and adaptive iterative optimization algorithm is proposed to counter suppressive jamming in information domain. Prior information of the linear frequency modulation (LFM) and suppressive jamming signals are fully used by constructing a joint sensing dictionary. The jamming sensing dictionary is further adaptively optimized to perfectly match actual jamming signals. Finally, through the precise reconstruction of the jamming signal, high detection precision of the original LFM signal is realized. The construction of sensing dictionary adopts the Pei type fast fractional Fourier decomposition method, which serves as an efficient basis for the LFM signal. The proposed adaptive iterative optimization algorithm can solve grid mismatch problems brought on by undetermined signals and quickly achieve higher detection precision. The simulation results clearly show the effectiveness of the method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2883-2902
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• 2023

Since the existing anti-jamming methods, including intelligent methods, have difficulty against high-speed reactive jamming, we studied a new methodology for jamming utilization instead of avoiding jamming. Different from the existing jamming utilization techniques that harvest energy from the jamming signal as a power supply, our proposed method can take the jamming signal as a favorable factor for frequency detection. Specifically, we design an intelligent differential frequency hopping communication framework (IDFH), which contains two stages of training and communication. We first adopt supervised learning to get the jamming rule during the training stage when the synchronizing sequence is sent. And then, we utilize the jamming rule to improve the frequency detection during the communication stage when the real payload is sent. Simulation results show that the proposed method successfully combated high-speed reactive jamming with different parameters. And the communication performance increases as the power of the jamming signal increase, hence the jamming signal can help users communicate in a low signal-to-noise ratio (SNR) environment.