• 전자공학회지
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• 제38권1호
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• pp.31-43
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• 2011

The mathematical foundations of the compressive sensing which goes against the common wisdom of data acquisition (the Nyquist-Shannon theorem) is reviewed. The compressive sensing asserts that one can reconstruct images or signals of interest accurately from a number of samples far smaller than the desired resolution of the image (e.g., the number of pixels in the image). The compressive sensing has far reaching implications. It suggests the new data acquisition protocols that translates analog information to digital form with fewer sensors considered necessary.

• 한국음향학회지
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• 제38권5호
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• pp.534-542
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• 2019

능동소나에서는 표적의 거리 도플러 정보를 탐지하기 위해 여러 가지 기법을 사용한다. 그중 압축 센싱을 적용한 기법은 기존의 방식보다 더욱 정밀한 탐지가 가능하며 우수한 성능을 나타낸다. 능동 소나의 거리 도플러 추정에 적용할 수 있는 압축 센싱 알고리즘은 여러 가지 있다. 압축 센싱 알고리즘 마다 계산 성능이 다르며 압축 센싱 알고리즘에 따라 신호 대 잡음비와 센싱 행렬의 코히런스가 거리 도플러 추정에 미치는 영향의 정도가 다르다. 본 논문은 능동 소나의 거리 도플러 추정을 위한 여러 가지 압축 센싱 알고리즘의 계산 성능과 정확도를 비교, 분석하였다. 여러 신호대 잡음비, 상호간섭성 값에 대한 OMP(Orthogonal Matching Pursuit), CoSaMP(Compressive Sampling Matching Pursuit), BPDN(CVX)(Basis Pursuit Denoising), LARS(Least Angle Regression) 알고리즘의 추정 성능을 확인하였으며, 상황에 따른 최적의 압축 센싱 알고리즘을 보인다.

• Smart Structures and Systems
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• 제22권2호
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• pp.231-237
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• 2018

A significant data problem is encountered with condition monitoring because the sensors need to measure vibration data at a continuous and sometimes high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate their efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer data than traditional data sampling methods. This sensing paradigm is applied to condition monitoring with an improved machine learning algorithm in this study. For the experiments, a built-in rotating system was used, and all data were compressively sampled to obtain compressed data. The optimal signal features were then selected without the signal reconstruction process. For damage classification, we used the Variance Considered Machine, utilizing only the compressed data. The experimental results show that the proposed compressive sensing method could effectively improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Computers and Concrete
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• 제6권3호
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• pp.225-234
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• 2009

Dredged silt from reservoirs in southern Taiwan was sintered to make lightweight aggregates (LWA), which were then used to produce lightweight aggregate concrete (LWAC).This study aimed to assess the compressive strength and homogeneity of LWAC using ultrasonic-echo sensing. Concrete specimens were prepared using aggregates of four different particle density, namely 800, 1100, 1300 and 2650 kg/$m^3$. The LWAC specimens were cylindrical and a square wall with core specimens drilled. Besides compressive strength test, ultrasonic-echo sensing was employed to examine the ultrasonic pulse velocity and homogeneity of the wall specimens and to explore the relationship between compressive strength and ultrasonic pulse velocity. Results show that LWA, due to its lower relative density, causes bloating, thus resulting in uneven distribution of aggregates and poor homogeneity. LWAC mixtures using LWA of particle density 1300 kg/$m^3$ show the most even distribution of aggregates and hence best homogeneity as well as highest compressive strength of 63.5 MPa. In addition, measurements obtained using ultrasonic-echo sensing and traditional ultrasonic method show little difference, supporting that ultrasonic-echo sensing can indeed perform non-destructive, fast and accurate assessment of LWAC homogeneity.

• Smart Structures and Systems
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• 제20권1호
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• pp.35-42
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• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.

• 한국음향학회지
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• 제38권5호
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• pp.522-533
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• 2019

거리-도플러 추정을 위한 압축센싱(Compressive Sensing,CS) 모델은 과소결정계인 y = Ax 선형시스템으로 표현할 수 있다. 압축센싱 기법으로 위 선형시스템의 해를 찾으려면 행렬 A가 충분히 비간섭적이고 x가 희소해야 한다. 본 연구는 행렬 A가 비간섭적이도록 행렬 A의 상호간섭성을 낮추는 동시에 소나시스템에서 요구하는 대역폭을 유지하는 송신파형 설계 방법을 제안하였다. 제안한 방법은 행렬사영으로 센싱행렬을 최적화하는 방법과 DFT(Discrete Fourier Transform) 행렬을 이용하여 원하지 않은 주파수밴드를 억압하는 두 가지 방법을 결합한 것이다. 정합필터와 압축센싱 기법을 이용하여 기존파형 LFM(Linear Frequency Modulated)과 설계한 파형의 거리-도플러 추정 성능을 비교하였다. 시뮬레이션을 통해 설계한 송신파형이 기존파형(LFM)보다 탐지성능이 우수함을 보인다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2014년도 하계학술대회
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• pp.230-231
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• 2014

Compressive sensing is a new sampling technique, which allows to sample a signal under the Nyquist-Shannon sampling rate. For block-based compressive sensing, a hybrid sensing matrix which contains low-frequency patterns in addition to the random Gaussian numbers is good for exploiting typical property of natural images. By noting that MH-BCS-SPL is well known for its good recovery performance, this paper investigates effect of the hybrid sensing matrix on MH-BCS-SPL in the sense of how large portion of low-frequency patterns can provide performance improvement.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.106-108
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• 2017

본 논문에서는 휘어지거나 굴곡진 array인 3차원 conformal array의 beam pattern을 보정하고자 기존의 2차원에서 3차원으로 확장한 interpolation technique과 compressive sensing을 이용하여 3-D uniform rectangular array(3-D URA)에 적용하는 방법을 연구하였다. 시뮬레이션 결과는 compressive sensing이 interpolation technique보다 우수한 특성을 보여준다.

• 한국통신학회논문지
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• 제40권6호
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• pp.1024-1031
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• 2015

압축 센싱은 신호가 성긴 (Sparse) 특성을 지니며 선형 측정된 값들이 Incoherent 할 때, 나이퀴스트율 이하로 표본화된 신호를 원본 신호로 정확하게 복구할 수 있는 새로운 신호 획득 이론이다. 본 논문에서는 원본 신호의 Sparse한 정도에 따라 성능이 변화하는 압축 센싱을 이용한 효율적인 신호 검출 및 추정 기법을 제안하며, 이론적 분석과 함께 모의 실험 결과를 보여준다.

• IEIE Transactions on Smart Processing and Computing
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• 제3권1호
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• pp.19-27
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• 2014

Compressive sensing is an emerging sampling technique which enables sampling a signal at a much lower rate than the Nyquist rate. In this paper, we propose a novel framework based on Kronecker compressive sensing that provides multi-resolution image reconstruction capability. By exploiting the relationship of the sensing matrices between low and high resolution images, the proposed method can reconstruct both high and low resolution images from a single measurement vector. Furthermore, post-processing using BM3D improves its recovery performance. The experimental results showed that the proposed scheme provides significant gains over the conventional framework with respect to the objective and subjective qualities.