• Title/Summary/Keyword: Mixed Noise Signal

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De-noising Method using Nonlinear Filter Algorithm in Mixed Noise Environments (복합잡음 환경에서 비선형 필터 알고리즘을 이용한 잡음제거 방법)

  • Long, Xu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.9
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    • pp.2265-2271
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    • 2014
  • In modern society digital equipments that are related with various hardware and software are popularized, and digital images are widely applied in the field of production and scientific research. In general, however, images are degraded by the noise in the process of transmission and storage. In this paper, to reduce the influence of mixed noises, the algorithm in which noises in the space area are classified into impulse noise and Gaussian noise and this is processed by applying weighted value, while that is processed by modified nonlinear filter is proposed. And the excellence of the proposed algorithm is judged by PSNR(peak signal to noise ratio).

Low cost 2.4-GHz VCO design in 0.18-㎛ Mixed-signal CMOS Process for WSN applications (저 가격 0.18-㎛ 혼성신호 CMOS공정에 기반한 WSN용 2.4-GHz 밴드 VCO설계)

  • Jhon, Heesauk;An, Chang-Ho;Jung, Youngho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.2
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    • pp.325-328
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    • 2020
  • This paper demonstrated a voltage-controlled oscillator (VCO) using cost-effective (1-poly 6-metal) mixed signal standard CMOS process. To have the high-quality factor inductor in LC resonator with thin metal thickness, patterned-ground shields (PGS) was adopted under the spiral to effectively reduce the ac current of low resistive Si substrate. And, because of thin top-metal compared with that of RF option (2 ㎛), we make electrically connect between the top metal (M6) and the next metal (M5) by great number of via array along the metal traces. The circuit operated from 2.48 GHz to 2.62 GHz tuned by accumulation-mode varactor device. And the measured phase noise of LC VCO has -123.7 dBc/Hz at 1MHz offset at 2.62 GHz and the dc-power consumption shows 2.07 mW with 1.8V supply voltage, respectively.

RBF Neural Networks-Based Adaptive Noise Filtering from the ECG Signal (방사기저함수 신경망을 기반한 ECG신호의 적응펄터링)

  • 이주원;이한욱;이종회;장두봉;김영일;이건기
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.1159-1162
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    • 1999
  • The ECG signal is very important information for diagnosis of patient and a cardiac disorder. It is hard to remove the noise because that is mixed with a lot of noise, and the error of the filtering will distort the ECG signal. The existing method for the filtering of the ECG signal has structure that has many steps for filtering, so that structure is complex and the processing speed is slow. For the improvement of that problem, we propose the method of filtering that has simple structure using the RBF neural networks and have good results.

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A Study on Blood Flow Measurement Method using Independent Component Analysis (독립성분분석을 이용한 혈류 속도 측정 방법에 관한 연구)

  • Cho, Seog-Bin;Lim, Dong-Seok;Baek, Kwang-Ryul
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.2 s.314
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    • pp.10-17
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    • 2007
  • The echo signal on ultrasonic transducer is a mixed signal from tissues, blood vessel walls, blood cells and noise. In this mixed-signal, the signal reflected from tissues and blood vessel walls is called clutter. It is necessary to extract pure blood signal from this mixed-signal, when measuring blood flow velocity with medical ultrasonic system The quality of measured blood flow velocity is highly dependent on sufficient attenuation of the clutter signals. In this paper, we suggest a clutter rejection method using ICA For simulation, the echo signals are generated by Field n ultrasonic simulation program In this echo signals, independent signals are separated by using ICA Then the blood signal is obtained from the separated signals. Blood flow velocity is measured by 2D autocorrelation method. We compare ICA clutter rejection method with PCA-based eigen filter method using both measured blood flow velocity profiles by 2D autocorrelation. In simulation results, ICA clutter rejection method can be better applied measuring blood flow velocity in noisy echo signals.

Nonlinear Composite Filter for Gaussian and Impulse Noise Removal (가우시안 및 임펄스 잡음 제거를 위한 비선형 합성 필터)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.3
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    • pp.629-635
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    • 2017
  • In this paper, we proposed a nonlinear synthesis filter for noise reduction to reduce the effects of Gaussian noise and impulse noise. When the centralization of the local mask is judged to be Gaussian noise by the noise judgment, the weight value of the weight filter are applied differently according to the spatial weight filter and the pixel change by using the sample variance in the local mask. And if it is determined as the impulse noise, we proposed an algorithm that applies different weights of local histogram weight filter and standard median filter according to noise density of mask. In order to evaluate the performance of the proposed filter algorithm, we used PSNR(peak signal to noise ratio) and compared existing methods and proposed filter algorithm in the mixed noise environment with Gaussian noise, impulsive noise, and two noises mixed.

Classification of Speech and Car Noise Signals using the Slope of Autocovariances in Frequency Domain (주파수 영역 자기 공분산 기울기를 이용한 음성과 자동차 소음 신호의 구분)

  • Kim, Seon-Il
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.10
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    • pp.2093-2099
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    • 2011
  • Speech signal and car noise signal such as muffler noise are segregated from the one which has both signals mixed using statistical method. To classify speech signal from the other in segregated signals, FFT coefficients were obtained for all segments of a signal where each segment consists of 128 elements of a signal. For several coefficients of FFT corresponding to the low frequencies of a signal, autocovariances are calculated between coefficients of same order of all segments of a signal. Then they were averaged over autocovariances. Linear equation was eatablished for the those autocovariances using the linear regression method for each siganl. The coefficient of the slope of the line gives reference to compare and decide what the speech signal is. It is what this paper proposes. The results show it is very useful.

Reducing the Effects of Noise Light in a Visible Light Communication System Using Two Color LEDs (가시광통신 시스템에서 2색 LED를 이용한 잡음광의 영향 감소)

  • Lee, Seong-Ho
    • Journal of Sensor Science and Technology
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    • v.21 no.6
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    • pp.429-433
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    • 2012
  • In this paper, we reduced the optical noise interference in a visible light communication system using two color LEDs. In the transmitter, the original and the inverted signals of the transmitted data modulated a red LED and a blue LED, respectively. In the receiver, a differential detector which is composed of two photodetectors and an optical red filter detected the mixed signal radiated from the two LEDs. In an environment that the optical noise from a fluorescent lamp exists, the signal-to-noise ratio in this system was improved by about 20dB compared to that in the conventional system which uses a single LED and a single photodetector.

Performance of music section detection in broadcast drama contents using independent component analysis and deep neural networks (ICA와 DNN을 이용한 방송 드라마 콘텐츠에서 음악구간 검출 성능)

  • Heo, Woon-Haeng;Jang, Byeong-Yong;Jo, Hyeon-Ho;Kim, Jung-Hyun;Kwon, Oh-Wook
    • Phonetics and Speech Sciences
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    • v.10 no.3
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    • pp.19-29
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    • 2018
  • We propose to use independent component analysis (ICA) and deep neural network (DNN) to detect music sections in broadcast drama contents. Drama contents mainly comprise silence, noise, speech, music, and mixed (speech+music) sections. The silence section is detected by signal activity detection. To detect the music section, we train noise, speech, music, and mixed models with DNN. In computer experiments, we used the MUSAN corpus for training the acoustic model, and conducted an experiment using 3 hours' worth of Korean drama contents. As the mixed section includes music signals, it was regarded as a music section. The segmentation error rate (SER) of music section detection was observed to be 19.0%. In addition, when stereo mixed signals were separated into music signals using ICA, the SER was reduced to 11.8%.

Partial EBG Structure with DeCap for Ultra-wideband Suppression of Simultaneous Switching Noise in a High-Speed System

  • Kwon, Jong-Hwa;Kwak, Sang-Il;Sim, Dong-Uk;Yook, Jong-Gwan
    • ETRI Journal
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    • v.32 no.2
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    • pp.265-272
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    • 2010
  • To supply a power distribution network with stable power in a high-speed mixed mode system, simultaneous switching noise caused at the multilayer PCB and package structures needs to be sufficiently suppressed. The uni-planar compact electromagnetic bandgap (UC-EBG) structure is well known as a promising solution to suppress the power noise and isolate noise-sensitive analog/RF circuits from a noisy digital circuit. However, a typical UC-EBG structure has several severe problems, such as a limitation in the stop band's lower cutoff frequency and signal quality degradation. To make up for the defects of a conventional EBG structure, a partially located EBG structure with decoupling capacitors is proposed in this paper as a means of both suppressing the power noise propagation and minimizing the effects of the perforated reference plane on the signal quality. The proposed structure is validated and investigated through simulation and measurement in both frequency and time domains.

A Study on Mixed Noise Removal using Modified Switching Filter (변형된 스위칭 필터를 이용한 복합잡음 제거에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.300-303
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    • 2015
  • Digital imaging process has been put to practical use in various application sectors due to a rapid advancement such as memory devices, etc. However, noises are being generated due to various reasons during the image processing and a variety of methods are being studied in order to eliminate these noises. Generally, images are damaged due to a mixed noise having different characteristics. In this paper, a filter algorithm which switches according to the noise types was proposed in order to mitigate the influence of mixed noise included in the image. And using the PSNR as the standard for objective decision making of the improvement effect, it was compared with the existing methods.

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