• Journal of Information Processing Systems
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• 제19권3호
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• 한국정보통신학회논문지
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• 제20권8호
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• pp.1452-1459
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• 2016

압축 센싱은 샤논/나이퀴스트 표본화 정리를 만족하는 나이퀴스트 율 보다 더 적은 수의 표본화 주파수로 신호를 획득하더라도 그 신호가 성긴 신호라는 조건 하에 샘플링을 가능하게 하는 신호 처리 기술이다. 일반적으로 측정 예측방식은 작은 블록 크기에서 성능이 좋은 반면에 복원 이미지 품질은 큰 블록으로 복원하는 것이 좋다. 이러한 두 개의 상충하는 속성을 해결하기 위해 압축 센싱은 작은 블록에서 행해지고, 복원은 큰 블록에서 수행하게 되는 구조화된 측정 행렬을 사용하며, 이러한 방법으로 예측과 복원 모두 동시에 개선을 추구한다. 본 논문에서는 구조화된 측정 행렬을 확장함으로써 블록 크기에 따른 다양한 방식이 비교되어진다. 다양한 실험 결과를 통해 $4{\times}4$ 하다마드 행렬을 이용한 구조화된 측정 행렬이 블록 크기가 4의 크기에서 가장 좋은 성능을 보여주었다.

• 한국통신학회논문지
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• 제41권12호
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• pp.1739-1741
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• 2016

OFDM 기반 통신시스템에서 압축 센싱을 단계적으로 적용하여 임펄스 잡음과 클리핑 잡음을 제거하는 방법을 제안한다. 이 방법은 1단계로 적응적 임계값을 적용한 블랭킹 기법을, 2단계 및 3단계에서 압축 센싱 기법을 반복적으로 적용하며 판정 궤환을 통해 비트 오율을 점차 감소시킨다. 임펄스 잡음 채널에서 모의실험결과 비트 오율이 $10^{-5}$일 때 4.5dB의 SNR 이득을 얻을 수 있었다.

• Current Optics and Photonics
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• 제5권6호
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• pp.606-616
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• 2021

A photonic integrated interferometric imaging system possesses the characteristics of small-scale, low weight, low power consumption, and better image quality. It has potential application for replacing conventional large space telescopes. In this paper, the principle of photonic integrated interferometric imaging is investigated. A novel lenslet array arrangement and lenslet pairing approach are proposed, which are helpful in improving spatial frequency coverage. For the novel lenslet array arrangement, two short interference arms were evenly distributed between two adjacent long interference arms. Each lenslet in the array would be paired twice through the novel lenslet pairing approach. Moreover, the image reconstruction model for optical interferometric imaging based on compressed sensing was established. Image simulation results show that the peak signal to noise ratio (PSNR) of the reconstructed image based on compressive sensing is about 10 dB higher than that of the direct restored image. Meanwhile, the normalized mean square error (NMSE) of the direct restored image is approximately 0.38 higher than that of the reconstructed image. Structural similarity index measure (SSIM) of the reconstructed image based on compressed sensing is about 0.33 higher than that of the direct restored image. The increased spatial frequency coverage and image reconstruction approach jointly contribute to better image quality of the photonic integrated interferometric imaging system.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2018년도 춘계 종합학술대회 논문집
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• pp.485-486
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• 2018

In this paper, we consider a binary recovery framework of the Compressed Sensing (CS) problem. We derive an upper bound for $L_0$ recovery performance of a binary sparse signal in terms of the dimension N and sparsity K of signals, the number of measurements M. We show that the upper bound obtained from this work goes to the limit bound when the sensing matrix sufficiently become dense. In addition, for perfect recovery performance, if the signals are very sparse, the sensing matrices required for $L_0$ recovery are little more dense.

• 대한전자공학회논문지TC
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• 제49권5호
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• pp.59-65
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• 2012

본 논문에서는 super-RENS 디스크의 채널 모델링을 위하여 압축 센싱 알고리즘에 기반한 sparse Volterra 필터에 대해 연구하였다. Super-RENS 디스크 시스템에서 심한 비선형 심벌간 간섭(ISI)이 발생하는 것은 익히 알려진 사실이다. 메모리를 가진 비선형 시스템은 Volterra 급수로 모델링할 수 있다. 또한, 압축 센싱은 측정치로부터 성긴 또는 압축된 신호를 복원할 수 있다. 이러한 이유로 super-RENS의 성긴 특성을 갖는 read-out 채널을 예측하기 위해 압축 센싱 알고리즘을 사용하였다. 평가 결과는 압축 센싱 알고리즘으로 super-RENS의 read-out 채널을 위한 sparse Volterra 모델을 효과적으로 구성할 수 있음을 보여준다.

• 한국인공지능학회지
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• 제6권1호
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• pp.1-10
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• 2018

Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.461-484
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• 2021

Compressed sensing in image reconstruction has attracted attention and many studies are proposed. As we know, adding prior knowledge about the distribution of the support on the original signal to CS can improve the quality of reconstruction. However, it is still difficult for a recovery framework adjusts its strategy for exploiting the prior knowledge efficiently according to the current estimated signals in serial iterations. With the theory of information geometry, we propose an adaptive strategy based on the current estimated signal in each iteration of the recovery. We also improve the performance of existing algorithms through the adaptive strategy for exploiting the prior knowledge according to the current estimated signal. Simulations are presented to validate the results. In the end, we also show the application of the model in the image.

• Investigative Magnetic Resonance Imaging
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• 제23권1호
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• pp.1-16
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• 2019

Dynamic contrast enhanced (DCE) magnetic resonance (MR) imaging plays an important role in non-invasive detection and characterization of primary and metastatic lesions in the liver. Recently, efforts have been made to improve spatial and temporal resolution of DCE liver MRI for arterial phase imaging. Review of recent publications related to arterial phase imaging of the liver indicates that there exist primarily two approaches: breath-hold and free-breathing. For breath-hold imaging, acquiring multiple arterial phase images in a breath-hold is the preferred approach over conventional single-phase imaging. For free-breathing imaging, a combination of three-dimensional (3D) stack-of-stars golden-angle sampling and compressed sensing parallel imaging reconstruction is one of emerging techniques. Self-gating can be used to decrease respiratory motion artifact. This article introduces recent MRI technologies relevant to hepatic arterial phase imaging, including differential subsampling with Cartesian ordering (DISCO), golden-angle radial sparse parallel (GRASP), and X-D GRASP. This article also describes techniques related to dynamic 3D image reconstruction of the liver from golden-angle stack-of-stars data.

• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 2007년도 학술대회
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• pp.69-69
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• 2007