• Title/Summary/Keyword: 신호 압축

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Audio Quality Enhancement using Perceptual Property at a Low-bitrate Compression (지각적 특성을 이용한 저 비트오율 압축 오디오 음질개선)

  • Cha Hyuk-Geun;Chae Byoung-Koog;Cha Hyung-Tai
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.275-278
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    • 2004
  • 본 논문에서는 저 비트오율 압축 시 발생되는 신호 왜곡을 인간의 지각적 특성을 이용하여 음질을 개선하는 알고리즘을 제안한다. 저 비트오율 압축 과정에서 손실된 고주파 영역의 신호를 부가 정보를 사용하지 않고 손실되지 않은 영역의 정보를 사용하여 고주파 영역의 신호를 첨가함으로써 음질을 개선하였다. 비 손실 영역의 순음 및 비 순음 성분을 검출하여 손실영역에 해당 하모닉 성분을 청각 자극 에너지로 스케일 하여 새로운 신호를 첨가한다. 원 신호와 저 비트오율 압축으로 인해 왜곡된 신호, 그리고 본 논문의 알고리즘을 이용하여 개선된 신호를 신호 대 잡음 비를 측정하고 청감 테스트를 통해 음질 개선 효과를 확인하였다.

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A Study on the Reconstruction of a Frame Based Speech Signal through Dictionary Learning and Adaptive Compressed Sensing (Adaptive Compressed Sensing과 Dictionary Learning을 이용한 프레임 기반 음성신호의 복원에 대한 연구)

  • Jeong, Seongmoon;Lim, Dongmin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37A no.12
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    • pp.1122-1132
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    • 2012
  • Compressed sensing has been applied to many fields such as images, speech signals, radars, etc. It has been mainly applied to stationary signals, and reconstruction error could grow as compression ratios are increased by decreasing measurements. To resolve the problem, speech signals are divided into frames and processed in parallel. The frames are made sparse by dictionary learning, and adaptive compressed sensing is applied which designs the compressed sensing reconstruction matrix adaptively by using the difference between the sparse coefficient vector and its reconstruction. Through the proposed method, we could see that fast and accurate reconstruction of non-stationary signals is possible with compressed sensing.

A new approach to enhancement of ground penetrating radar target signals by pulse compression (파형압축 기법에 의한 GPR탐사 반사신호 분해능 향상을 위한 새로운 접근)

  • Gaballah, Mahmoud;Sato, Motoyuki
    • Geophysics and Geophysical Exploration
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    • v.12 no.1
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    • pp.77-84
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    • 2009
  • Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe. The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.

16kbps Windeband Sideband Speech Codec (16kbps 광대역 음성 압축기 개발)

  • 박호종;송재종
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.1
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    • pp.5-10
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    • 2002
  • This paper proposes new 16 kbps wideband speech codec with bandwidth of 7 kHz. The proposed codec decomposes the input speech signal into low-band and high-band signals using QMF (Quadrature Mirror Filter), then AMR (Adaptive Multi Rate) speech codec processes the low-band signal and new transform-domain codec based on G.722.1 wideband cosec compresses the high-band signal. The proposed codec allocates different number of bits to each band in an adaptive way according to the property of input signal, which provides better performance than the codec with the fixed bit allocation scheme. In addition, the proposed cosec processes high-band signal using wavelet transform for better performance. The performance of proposed codec is measured in a subjective method. and the simulations with various speech data show that the proposed coders has better performance than G.722 48 kbps SB-ADPCM.

Nondestructive Assessment of Compressive Strength of Construction Materials Using Impact-Echo Response Signal (임팩에코 응답신호를 적용한 건설재료 비파괴 압축강도 산정)

  • Son, Moorak;Kim, Moojun
    • Journal of the Korean GEO-environmental Society
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    • v.18 no.8
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    • pp.17-21
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    • 2017
  • This paper is to grasp the use of impact-echo response signal induced from impacting an object for the assessment of compressive strength of construction materials nondestructively and to propose the test results. For this study, an impact device was devised and used for impacting an object by an initial rotating free falling impact and following repetitive impacts from the rebound action which eventually disappears. Concrete test specimens which had been mixed for different strengths were tested and the impact echo response signal was measured for each test specimen. The total sound signal energy which is assessed from integrating the impact-echo response signal was compared with the directly measured compressive strength for each specimen. The comparison showed that the total sound signal energy has a direct relationship with the directly measured compressive strength and the results clearly indicated that the compressive strength of construction materials can be assessed nondestructively using total sound signal energy which is assessed from integrating the impact-echo response signal induced from impacting an object.

A Pilot Study on Nondestructive Assessment of Compressive Strength Using Impact Force Response Signal (충격력 응답신호를 이용한 비파괴 압축강도 산정에 관한 기초연구)

  • Son, Moorak;Choi, Yoonseo
    • Journal of the Korean GEO-environmental Society
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    • v.20 no.4
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    • pp.5-9
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    • 2019
  • This paper is to provide the results of a pilot study of the usability and possibility of impact force response signal induced from impacting an object for the assessment of compressive strength of various materials (rock, concrete, wood, etc.) nondestructively. For this study, a device was devised for impacting an object and measuring the impact force. The impact was carried out by an initial rotating free falling impact and following repetitive impacts from the rebound action which eventually disappears. Wood and rock test specimens for different strengths were tested and an impact force response signal was measured for each test specimen. The total impact force signal energy which is assessed from integrating the impact force response signal was compared with the directly measured compressive strength for each specimen. The comparison showed that the total impact force signal energy has a direct relationship with the directly measured compressive strength and the results clearly indicated that the compressive strength of construction materials can be assessed nondestructively using total impact force signal energy which is assessed from integrating the impact force response signal induced from impacting an object.

ECG Signal Compression based on Adaptive Multi-level Code (적응적 멀티 레벨 코드 기반의 심전도 신호 압축)

  • Kim, Jungjoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.6
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    • pp.519-526
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    • 2013
  • ECG signal has the feature that is repeated in a cycle of P, Q, R, S, and T waves and is sampled at a high sampling frequency in general. By using the feature of periodic ECG signals, maximizing compression efficiency while minimizing the loss of important information for diagnosis is required. However, the periodic characteristics of such amplitude and period is not constant by measuring time and patients. Even though measured at the same time, the patient's characteristics display different periodic intervals. In this paper, an adaptive multi-level coding is provided by coding adaptively the dominant and non-dominant signal interval of the ECG signal. The proposed method can maximize the compression efficiency by using a multi-level code that applies different compression ratios considering information loss associated with the dominant signal intervals and non-dominant signal intervals. For the case of long time measurement, this method has a merit of maximizing compression ratio compared with existing compression methods that do not use the periodicity of the ECG signal and for the lossless compression coding of non-dominant signal intervals, the method has an advantage that can be stored without loss of information. The effectiveness of the ECG signal compression is proved throughout the experiment on ECG signal of MIT-BIH arrhythmia database.

Selective Quantization Based on Band Property for Wideband Signal Codec (광대역 신호 압축기를 위한 주파수 대역 특성에 선택적인 양자화 방법)

  • 송재종;박호종;김무영;김도석;김정수
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.7
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    • pp.76-82
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    • 2001
  • In this paper, a novel quantization method for wideband signal codec with 7 kHz bandwidth is proposed. In the transform-based wideband signal codecs, the signal is transformed to frequency domain and the spectral coefficients in each frequency band are quantized based on human perceptual model, followed by Huffman coding. However, the property of each band varies with frequency, and the codec has poor performance when all bands are quantized with the same method. Therefore, a selective quantization method is proposed, which analyzes the band property and selects the quantization domain between frequency domain and time domain based on the quantization efficiency. It is confirmed that the proposed method has better performance than the quantizer of G722.1 codec.

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Study on Non-destructive Assessment of Compressive Strength of Rock Using Impact Force Response Signal (타격력 응답신호를 이용한 암석의 비파괴 압축강도 산정방법에 관한 연구)

  • Son, Moorak;Seong, Jinhyun
    • Journal of the Korean GEO-environmental Society
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    • v.23 no.10
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    • pp.13-19
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    • 2022
  • This paper is to provide the results of usability of the impact force response signal induced from initial and successive rebound impacting a rock specimen for assessing the compressive strength of rock non-destructively. For this study, a device was devised for impacting a rock specimen and a system for measuring the impact force was set up. The impact was carried out by an initial rotating free falling impact and following repetitive impacts from the rebound action which eventually disappears. Three different kinds of rock specimen were tested and an impact force response signal was measured for each test specimen. The total impact force signal energy which is assessed from integrating the impact force response signal induced from initial and rebound impacts was compared with the directly measured compressive strength for each rock specimen. The comparison showed that the total impact force signal energy has a direct relationship with the directly measured compressive strength and the results clearly indicated that the compressive strength of rock can be assessed non-destructively using total impact force signal energy.

Cooperative Bayesian Compressed Spectrum Sensing for Correlated Signals in Cognitive Radio Networks (인지 무선 네트워크에서 상관관계를 갖는 다중 신호를 위한 협력 베이지안 압축 스펙트럼 센싱)

  • Jung, Honggyu;Kim, Kwangyul;Shin, Yoan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38B no.9
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    • pp.765-774
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    • 2013
  • In this paper, we present a cooperative compressed spectrum sensing scheme for correlated signals in decentralized wideband cognitive radio networks. Compressed sensing is a signal processing technique that can recover signals which are sampled below the Nyquist rate with high probability, and can solve the necessity of high-speed analog-to-digital converter problem for wideband spectrum sensing. In compressed sensing, one of the main issues is to design recovery algorithms which accurately recover original signals from compressed signals. In this paper, in order to achieve high recovery performance, we consider the multiple measurement vector model which has a sequence of compressed signals, and propose a cooperative sparse Bayesian recovery algorithm which models the temporal correlation of the input signals.