• Title/Summary/Keyword: Signal-to-noise ratio improvement

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A Study on the Performance Improvement of Software Digital Filter using GPU (GPU를 이용한 소프트웨어 디지털 필터의 성능개선에 관한 연구)

  • Yeom, Jae-Hwan;Oh, Se-Jin;Roh, Duk-Gyoo;Jung, Dong-Kyu;Hwang, Ju-Yeon;Oh, Chungsik;Kim, Hyo-Ryoung
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.4
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    • pp.153-161
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    • 2018
  • This paper describes the performance improvement of Software (SW) digital filter using GPU (Graphical Processing Unit). The previous developed SW digital filter has a problem that it operates on a CPU (Central Processing Unit) basis and has a slow speed. The GPU was introduced to filter the data of the EAVN (East Asian VLBI Network) observation to improve the operation speed and to process data with other stations through filtering, respectively. In order to enhance the computational speed of the SW digital filter, NVIDIA Titan V GPU board with built-in Tensor Core is used. The processing speed of about 0.78 (1Gbps, 16MHz BW, 16-IF) and 1.1 (2Gbps, 32MHz BW, 16-IF) times for the observing time was achieved by filtering the 95 second observation data of 2 Gbps (512 MHz BW, 1-IF), respectively. In addition, 2Gbps data is digitally filtered for the 1 and 2Gbps simultaneously observed with KVN (Korean VLBI Network), and compared with the 1Gbps, we obtained similar values such as cross power spectrum, phase, and SNR (Signal to Noise Ratio). As a result, the effectiveness of developed SW digital filter using GPU in this research was confirmed for utilizing the data processing and analysis. In the future, it is expected that the observation data will be able to be filtered in real time when the distributed processing optimization of source code for using multiple GPU boards.

Development of Position Sensor Detection Circuit using Hall Effect Sensor (Hall Effect Sensor를 이용한 위치센서 검출회로개발)

  • Jeong, Sungin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.2
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    • pp.143-149
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    • 2021
  • BLDC motors are getting better performance due to the improvement of material technology including high performance of permanent magnets, advancement of driving IC technology with high integration and high functionality, and improvement of assembly technology such as high point ratio. While having the advantage of such a square wave driven BLDC motor, interest in the design and development of a square wave driven BLDC permanent magnet motor and development of a position detection circuit and driver is increasing in order to more meet the needs of users. However, in spite of the cost and functional advantages due to reduced efficiency, switching loss and vibration, noise, etc., the application is somewhat limited. Therefore, in this paper, we study a position detection circuit that generates a sinusoidal signal in proportion to the magnetic flux of a BLDC motor rotor using a Hall Effect Sensor that generates a sinusoidal wave to increase the efficiency of the motor, reduce ripple, and drive a sinusoidal current with excellent speed and torque characteristics.

Voice Activity Detection Using Modified Power Spectral Deviation Based on Teager Energy (Teager Energy 기반의 수정된 파워 스펙트럼 편차를 이용한 음성 검출)

  • Song, J.H.;Song, Y.R.;Shim, H.M.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.8 no.1
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    • pp.41-46
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    • 2014
  • In this paper, we propose a novel voice activity detection (VAD) algorithm using feature vectors based on TE (teager energy). Specifically, power spectral deviation (PSD), which is used as the feature for the VAD in the IS-127 noise suppression algorithm, is obtained after the input signal is transfomed by Teager energy operator. In addition, the TE-based likelihhod ratio are derived in each frame to modifiy the PSD for further VAD. The performance of our proposed VAD algorithm are evaluated by objective testing (total error rate, receiver operating characteristics, perceptual evaluation of speech quality) under various environments, and it is found that the proposed method yields better results than conventional VAD algorithms in the non-stationary noise environments under 5 dB SNR (total error rate = 2.6% decrease, PESQ score = 0.053 improvement).

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Performance Analysis of the Packet DS/SS Receiver using the BSP Methods (패킷 대역 확산 블록 수신기의 성능 분석)

  • 양대웅;강민구;박성경;홍대식;강창언
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.1
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    • pp.47-55
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    • 1994
  • This paper investigates the performance analysis of the packet DS/SS receiver with a PJED(phase-jump error detector) using the block signal processing(BSP) methods. The conventional packet DS/SS block receiver has a high probability of mistaking the phase-jump detection, which causes the frequency estimation error. The conventional receiver uses a Matched-Pulse Timing Extractor which has a complicated structure. The proposed packet DS/SS block receiver with the PJED which uses libearity of the phase has little probability of mistaking the phase-jump detection. The proposed Matched Pulse Timing Extractor gas the more simple structure but obtains the same performance on the exact matched-pluse timing as the conventional one does. The simulation results show that the proposed receiver gives about 2dB improvement in the BER compared with the conventional receiver.

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An effective quality improvement scheme of magnified image using the surface characteristics in image (영상의 곡면 특성을 활용한 효과적인 확대영상의 화질 향상 기법)

  • Jung, Soo-Mok;On, Byung-Won
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.8
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    • pp.45-54
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    • 2014
  • In this paper, we proposed an effective quality improvement scheme of magnified image using the surface characteristics in image. If the surface in image is estimated as simple convex surface or simple concave surface, the interpolated value can be calculated to have the surface characteristics by using the other method in the proposed scheme. The calculated value becomes the interpolated pixel value inmagnified image. So, themagnified image reflects the surface characteristics of the real image. If the surface is not estimated as simple convex surface or simple concave surface, the interpolated value is calculated more accurately than bilinear interpolation by using the method of the proposed scheme. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

  • Chenggong Yan;Jie Lin;Haixia Li;Jun Xu;Tianjing Zhang;Hao Chen;Henry C. Woodruff;Guangyao Wu;Siqi Zhang;Yikai Xu;Philippe Lambin
    • Korean Journal of Radiology
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    • v.22 no.6
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    • pp.983-993
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    • 2021
  • Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

New Frequency-domain GSC using the Modified-CFAR Algorithm (변형된 CFAR 알고리즘을 이용한 새로운 주파수영역 GSC)

  • Cho, Myeong-Je;Moon, Sung-Hoon;Han, Dong-Seog;Jung, Jin-Won;Kim, Soo-Joong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.2
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    • pp.96-107
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    • 1999
  • The generalized sidelobe cancellers(GSC's) ar used for suppressing an interference in array radar. The frequency-domain GSC's have a faster convergence rate than the time-domain GSC's because they remove the correlation between the interferences using a frequency-domain least mean square(LMS) algorithm. However, we have not fully used the advantage of the frequency-domain GSC's since we have always updated the weights of all frequency bins, even the interferer free frequency bin. In this paper, we propose a new frequency-domain GSC based on constant false-alarm rate(CFAR) detector, of which GSC adaptively determine the bin whose weight is updated according to the power of each frequency bin. This canceller updates the weight of only updated according to the power of each frequency bin. This canceller updates the weight of only the bin of which the power is high because of the interference signal. The computer simulation shows that the new GSC reduces the iteration number for convergence over the conventional GSC's by more than 100 iterations. The signal-to-noise ration(SNR) improvement is more than 5 dB. Moreover, the number of renewal weights required for the adaptation is much fewer than that of the conventional one.

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Improvement of Analytic Reconstruction Algorithms Using a Sinogram Interpolation Method for Sparse-angular Sampling with a Photon-counting Detector

  • Kim, Dohyeon;Jo, Byungdu;Park, Su-Jin;Kim, Hyemi;Kim, Hee-Joung
    • Progress in Medical Physics
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    • v.27 no.3
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    • pp.105-110
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    • 2016
  • Sparse angular sampling has been studied recently owing to its potential to decrease the radiation exposure from computed tomography (CT). In this study, we investigated the analytic reconstruction algorithm in sparse angular sampling using the sinogram interpolation method for improving image quality and computation speed. A prototype of the spectral CT system, which has a 64-pixel Cadmium Zinc Telluride (CZT)-based photon-counting detector, was used. The source-to-detector distance and the source-to-center of rotation distance were 1,200 and 1,015 mm, respectively. Two energy bins (23~33 keV and 34~44 keV) were set to obtain two reconstruction images. We used a PMMA phantom with height and radius of 50.0 mm and 17.5 mm, respectively. The phantom contained iodine, gadolinium, calcification, and lipid. The Feld-kamp-Davis-Kress (FDK) with the sinogram interpolation method and Maximum Likelihood Expectation Maximization (MLEM) algorithm were used to reconstruct the images. We evaluated the signal-to-noise ratio (SNR) of the materials. The SNRs of iodine, calcification, and liquid lipid were increased by 167.03%, 157.93%, and 41.77%, respectively, with the 23~33 keV energy bin using the sinogram interpolation method. The SNRs of iodine, calcification, and liquid state lipid were also increased by 107.01%, 13.58%, and 27.39%, respectively, with the 34~44 keV energy bin using the sinogram interpolation method. Although the FDK algorithm with the sinogram interpolation did not produce better results than the MLEM algorithm, it did result in comparable image quality to that of the MLEM algorithm. We believe that the sinogram interpolation method can be applied in various reconstruction studies using the analytic reconstruction algorithm. Therefore, the sinogram interpolation method can improve the image quality in sparse-angular sampling and be applied to CT applications.

HeNB-Aided Virtual-Handover for Range Expansion in LTE Femtocell Networks

  • Tang, Hao;Hong, Peilin;Xue, Kaiping
    • Journal of Communications and Networks
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    • v.15 no.3
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    • pp.312-320
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    • 2013
  • Home evolved Node-B (HeNB), also called a femtocell or a femto base station, is introduced to provide high data rate to indoor users. However, two main problems arise in femtocell networks: (1) Small coverage area of HeNB, which results in limited cell-splitting gain and ping-pong handover (HO) problems and (2) high inter-femtocell interference because HeNBs may be densely deployed in a small region. In this study, an efficient cooperation mechanism called an HeNB-aided virtual-HO (HaVHO) scheme is proposed to expand the coverage area of femtocells and to reduce inter-femtocell interference. The cooperation among neighbor HeNBs is exploited in HaVHO by enabling an HeNB to relay the data of its neighbor HeNB without an HO. The HaVHO procedure is compatible with the existing long term evolution specification, and the information exchange overhead in HaVHO is relatively low. To estimate the signal to interference plus noise ratio improvement, the area average channel state metric is proposed, and the amount of user throughput enhancement by HaVHO is derived. System-level simulation shows that HaVHO has a better performance than the other four schemes, such as lesser radio link failure, lesser ping-pong handover, lesser short-stay handover, and higher user throughput.

Improved Recognition of Far Objects by using DPM method in Curving-Effective Integral Imaging (커브형 집적영상에서 부분적으로 가려진 먼 거리 물체 인식 향상을 위한 DPM 방법)

  • Chung, Han-Gu;Kim, Eun-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.2A
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    • pp.128-134
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    • 2012
  • In this paper, we propose a novel approach to enhance the recognition performance of a far and partially occluded three-dimensional (3-D) target in computational curving-effective integral imaging (CEII) by using the direct pixel-mapping (DPM) method. With this scheme, the elemental image array (EIA) originally picked up from a far and partially occluded 3-D target can be converted into a new EIA just like the one virtually picked up from a target located close to the lenslet array. Due to this characteristic of DPM, resolution and quality of the reconstructed target image can be highly enhanced, which results in a significant improvement of recognition performance of a far 3-D object. Experimental results reveal that image quality of the reconstructed target image and object recognition performance of the proposed system have been improved by 1.75 dB and 4.56% on the average in PSNR (peak-to-peak signal-to-noise ratio) and NCC (normalized correlation coefficient), respectively, compared to the conventional system.