• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.260-263
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• 2005

본 논문에서는 차세대 유무선 광대역 통합망에서 실시간 멀티미디어의 응용 계층 품질을 평가하기 위한 실시간 음성 전송 플랫폼 라이브러리를 개발하였다. 개발된 라이브러리는 실시간 음성 통신시 사용자가 요구할 수 있는 다양한 품질을 제공하기 위해 전송률과 압축 방식에 따른 음성 코덱들을 포함하고 있다. 본 라이브러리는 다양한 환경에도 동일 입출력, 다중스레드, 인터넷 통신 등이 가능한 PWLIB를 기반으로 한다. 음성 데이터는 RTP/UDP/IP를 이용하여 패킷화되고 RTCP를 이용하여 전송 품질이 모니터링된다. 개발된 음성 통신 라이브러리를 이용하여 간단한 음성 통신 시스템을 구현하였으며, 음성 코덱별로 네트워크 상에서 송수신 테스트를 진행하였다. 본 라이브러리는 비디오 코덱 및 시그널링 및 네트웍 자원 예약 프로토콜과 결합되어 멀티미디어 통신 단말 개발에 사용 될 수 있다.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

• Journal of IKEEE
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• v.24 no.4
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• pp.1122-1128
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• 2020

Bandwidth Extension refers to restoring and expanding a narrow band signal(NB) that is damaged or damaged in the encoding and decoding process due to the lack of channel capacity or the characteristics of the codec installed in the mobile communication device. It means converting to a wideband signal(WB). Bandwidth extension research mainly focuses on voice signals and converts high bands into frequency domains, such as SBR (Spectral Band Replication) and IGF (Intelligent Gap Filling), and restores disappeared or damaged high bands based on complex feature extraction processes. In this paper, we propose a model that outputs an bandwidth extended signal based on an autoencoder among deep learning models, using the residual connection of one-dimensional convolutional neural networks (CNN), the bandwidth is extended by inputting a time domain signal of a certain length without complicated pre-processing. In addition, it was confirmed that the damaged high band can be restored even by training on a dataset containing various types of sound sources including music that is not limited to the speech.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.5-9
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• 2001

In this paper, we propose the new audio watermarking method and can be used on line processing. Instead of the wavelet transform, we use the integer wavelet transform for the reduction of the computational load. The watermark associated with the chi-square distribution is inserted into the signal on the integer wavelet domain. When extracting the watermark, the spread spectrum methods are used with the coefficients associated with the covariance sequence. We show that the chi-square distribution is a good tool for the spread spectrum method on the wavelet domain. This watermarking technique may be used for the control of the electrical product which can be controlled with the hidden signals and can be moved according to the audible signals simultaneously.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.391-399
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• 2018

In this paper, we construct and compare various guitar chord classification systems using perceptron neural network and convolutional neural network without pre-processing other than Fourier transform to identify the optimal chord classification system. Conventional guitar chord classification schemes use, for better feature extraction, computationally demanding pre-processing techniques such as stochastic analysis employing a hidden markov model or an acoustic data filtering and hence are burdensome for real-time chord classifications. For this reason, we construct various perceptron neural networks and convolutional neural networks that use only Fourier tranform for data pre-processing and compare them with dataset obtained by playing an electric guitar. According to our comparison, convolutional neural networks provide optimal performance considering both chord classification acurracy and fast processing time. In particular, convolutional neural networks exhibit robust performance even when only small fraction of low frequency components of the data are used.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.39-42
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• 1998

본 논문에서는 방송용 오디오 기기가 갖는 다채널의 특성과 각 채널에 대한 다양한 신호처리 기능의 특성을 고려하여 다채널 디지털 오디오 신호 처리기의 구조를 제안하고 범용 DSP를 이용하여 실시간 병렬 처리 시스템을 구현하였다. 구현된 시스템은 32비트 부동수소점 DSP를 이용하였으며 스테레오 채널의 48KHz 표본화 주파수를 지원하고 20비트 해상도를 갖는 시스템이다. 다채널 디지털 오디오 신호 처리 시스템의 구조는 디지털 신호 처리 과정을 수행하는 디지털 오디오 데이터 처리 부분과 시스템을 제어하기 위한 제어 정보 처리 부분으로 제안하였다. 이러한 구조에 적합한 실시간 시스템을 구현하기 위해 전체 시스템은 4부분의 모듈로 구성된다.

• Journal of Biomedical Engineering Research
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• v.7 no.1
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• pp.75-79
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• 1986

In this paper, a multigate pulsed doppler system with parallel signal processing which enables the transcutaneous assesment of the blood-flow velocities of five adjacent sample volumes is developed. The outputs of the system are audio signals, velocity curves and velocity profiles of 5 adjacent sample volumes. We have applied to the major superficial arteries and obtained the detailed information about the time dependent blood-flow behavior.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.419-421
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• 2006

The importance of automatic discrimination image data has evolved as a research topic over recent years. We have used forward neural network as a classifier using sound data features within image data, our initial tests have shown encouraging results that indicate the viability of our approach.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.131-135
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• 2009

This paper is the introduction of our work on distributed load scheduling in single-level tree network. In this paper, we derive a new calculation model in single-level tree network and show a closed-form formulation of the time for computation system. There are so many examples of the application of this technology such as distributed database, biology computation on genus, grid computing, numerical computing, video and audio signal processing, etc.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.149-152
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• 2002

The performance of a 1-bit DAC depends on that of the analog circuits. The mixed SC-CT (switched capacitor-continuous time) architecture is an effective design methodology for the analog circuits. This paper Proposes a new buffer scheme for the 1-bit digital-to-analog subconverter and a new SF-DSC(smoothing filter and differential-to-sig le converter) which performs both the smoothing filter and the differential-to-single convertor simultaneously.