• Title/Summary/Keyword: 주파수가중치

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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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Suppression of side lobe and grating lobe in ultrasound medical imaging system (의료용 초음파 영상 시스템에서 부엽과 격자엽의 억제)

  • Jeong, Mok Kun
    • The Journal of the Acoustical Society of Korea
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    • v.41 no.5
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    • pp.525-533
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    • 2022
  • We propose an effective method for suppressing both side and grating lobes by applying 2-dimensional Fourier Transform to the received channel data during the receive focusing process of an ultrasound imaging system. When the signal from the image point is focused, the channel signals have the same DC value across the channels. However, even after echoes from outside an imaging point are focused, they are manifested as having different spatial frequencies depending on their incident angles. Therefore, after the receive focusing delay time is applied, 2-D Fourier Transform is performed on the time-channel data to separate the DC component and other frequency components in the spectral domain, and the weighting value is defined using the ratio of the two values. The side lobe and grating lobe were suppressed by multiplying the ultrasound image by a weighting value. Ultrasound images with a frequency of 5 MHz were simulated in a 64-channel linear array. The grating lobe appearing in the ultrasound image was completely removed by applying the proposed method. In addition, the side lobe was reduced and the lateral resolution was greatly increased. Results of computer simulation on a human organ mimicking image show that the proposed method can aid in better lesion diagnosis by increasing the image contrast.

A study on weighting algorithm of multi-band transmission method using an estimated BER (추정 BER을 이용한 다중 밴드 전송 기법의 가중치 알고리즘 연구)

  • Shin, Ji-Eun;Jeong, Hyun-Woo;Jung, Ji-Won
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.4
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    • pp.359-369
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    • 2021
  • In underwater communications, to compensate performance degradation induced from rapidly changing channel transfer characteristic, multi-band communication method which allocate the same data to different frequency bands is used. However, the multi-band configuration may have worse performance than the single-band one because performance degradation in a particular band affects the output from the entire bands. This problem can be solved through a receiving end that analyzes error rates of each band, sets threshold values and allocates lower weights to inferior bands. Therefore, this paper proposed a weighting algorithm based on estimated Bit Error Rate (BER) which analyzes reliability of received data based on the performance difference between demodulated and decoded data. Employing turbo codes with coding rate of 1/3, we evaluate the performance of the proposed weighted multi-band transmission model in real underwater environments based on optimal simulation parameters. Through the sea trial experiment, we confirmed error performance was improved by applying the proposed weighting algorithm.

Effect of Low Frequency Vibration on Human and Its Application (저주파수 진동이 인체에 미치는 영향과 응용(ISO 2631-3 내용을 중심으로))

  • 장한기
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.823-827
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    • 2001
  • 인체에 영향을 미치는 진동을 분류하는데 가장 중요한 기준은 주파수이다. ISO의 인체진동관련 규격에서는 인체에 영향을 미치는 거동을 저주파수 운동(0.63Hz이하)과 진동(1~80Hz)으로 나누고 있다[1]. ISO 2631에서는 주파수별로 인체에 미치는 영향을 그림1과 같이 가중치로 정의하여 제시하고 있다. 저주파수 영역의 운동은 외부 거동(주로 수평방향)에 대하여 자세를 유지하기 위해 힘Tm게 되므로 물리적인 피로감을 줄 뿐만 아니라 'Motion sickness'란 증상을 유발한다.(중략)

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A Voice Boundary Detection Method Using Dynamic Parameters Based On Neural Network (신경망 기반의 동적 파라미터들을 이용한 음성 경계 추출)

  • 마창수;김계영;최형일
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.616-618
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    • 2002
  • 본 논문에서는 음성인식 성능을 높이기 위한 기본적 단계인 음성과 비음성 부분의 경계를 추출하는 음성 경계 추출 방법을 제안한다. 음성경계 추출을 위한 특징들로는 시간영역 분할 파라미터인 ZCR, MA를 사용하고 주파수 영역 분할 파라미터로 주파수 대역 파워 에너지 (Frequency band power energy), 포만트 계수 (Formant coefficient)를 사용하였고 각 파라미터들을 이용하여 음성 경계를 결정할 때 경험에 의해 임계치를 결정하는 단점을 보안하기 위해서 신경망을 이용한다. 신경망의 가중치와 임계치들은 지도 학습을 통해 최적화 되고, 학습을 통해 구성된 망을 음성과 비음성의 경계치 구분에 사용한다.

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Improvement of Perceptual Quality of HEVC by Rate Distortion Optimization Using Frequency Domain Structural Similarity (주파수 도메인의 구조적 유사도를 통한 HEVC 주관적 화질 향상 율-왜곡 최적화)

  • Jung, Sanghyun;Jeon, Byuengwoo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.06a
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    • pp.81-82
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    • 2017
  • 본 논문에서는 PSNR 을 높이도록 최적화된 HEVC 의 율-왜곡 최적화(RDO)를 MS-SSIM 를 높이도록 하여 RDO 를 수행 하도록 한다. 구현 방법으로는 MS-SSIM 도출 방법과 비슷하도록 원본과 4 단계의 저역 통과 필터(LPF)를 통과한 결과에 대한 DCT(Discrete Cosine Transform) 를 수행하고 그 AC 계수의 비율로 lagrange multiplier(${\lambda}$)를 수정하는 방식이다. AC 계수 비율과 MS-SSIM 에서 도출 된 가중치, LPF 특성 등에 따라 새롭게 각 스케일의 가중치를 결정하여 최종적으로 ${\lambda}$ 가중치를 결정하여 그 결과를 바탕으로 RDO 를 수행한다. 시뮬레이션을 통해 제안의 방법과 HEVC reference software 의 BD-rate 계산 결과 7%의 PNSR, -13.2%의 MS-SSIM 를 얻을 수 있었고 이에 따라 주관적 화질을 개선했다고 할 수 있다.

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Voice Activity Detection Based on Real-Time Discriminative Weight Training (실시간 변별적 가중치 학습에 기반한 음성 검출기)

  • Chang, Sang-Ick;Jo, Q-Haing;Chang, Joon-Hyuk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.4
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    • pp.100-106
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    • 2008
  • In this paper we apply a discriminative weight training employing power spectral flatness measure (PSFM) to a statistical model-based voice activity detection (VAD) in various noise environments. In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratio test (LRT) based on a minimum classification error (MCE) method which is different from the previous works in th at different weights are assigned to each frequency bin and noise environments depending on PSFM. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LRT.

Bit-level Array Structure Representation of Weight and Optimization Method to Design Pre-Trained Neural Network (학습된 신경망 설계를 위한 가중치의 비트-레벨 어레이 구조 표현과 최적화 방법)

  • Lim, Guk-Chan;Kwak, Woo-Young;Lee, Hyun-Soo
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.39 no.9
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    • pp.37-44
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    • 2002
  • This paper proposes efficient digital hardware design method by using fixed weight of pre-trained neural network. For this, arithmetic operations of PEs(Processing Elements) are represented with matrix-vector multiplication. The relationship of fixed weight and input data present bit-level array structure architecture which is consisted operation node. To minimize the operation node, this paper proposes node elimination method and setting common node depend on bit pattern of weight. The result of FPGA simulation shows the efficiency on hardware cost and operation speed with full precision. And proposed design method makes possibility that many PEs are implemented to on-chip.

Discriminative Weight Training for a Statistical Model-Based Voice Activity Detection (통계적 모델 기반의 음성 검출기를 위한 변별적 가중치 학습)

  • Kang, Sang-Ick;Jo, Q-Haing;Park, Seung-Seop;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.5
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    • pp.194-198
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    • 2007
  • In this paper, we apply a discriminative weight training to a statistical model-based voice activity detection(VAD). In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratios(LRs) based on a minimum classification error(MCE) method which is different from the previous works in that different weights are assigned to each frequency bin which is considered more realistic. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LR test.

Performance Analysis of Data Association Applied Frequency Weighting in 3-Passive Linear Array Sonars (주파수 가중치를 적용한 3조의 수동 선배열 소나 센서의 정보 연관 성능 분석)

  • 구본화;윤제한;홍우영;고한석
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.2
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    • pp.109-116
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    • 2004
  • This paper deals with data association using 3 sets of passive linear array sonars (PUS) geometrically positioned in a Y-shaped configuration, but fixed in an underwater environment. The data association problem is directly transformed into a 3-D assignment problem, which is known to be NP-hard. For generic passive sensors, it can be sotted using conventional algorithms, while it in PLAS becomes a formidable task due to the presence of bearing ambiguity. In particular, we proposed data association method robust to bearing measurements errors by incorporating frequency information and analyze a region of ghost problem by geometrical relation PUS and target. We analyzed the effectiveness of the proposed method by representative simulation in multi-target.