• Title/Summary/Keyword: Source separation

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Post-Processing with Frequency Domain Wiener Filter for Blind Source Separation

  • Park, Keun-Soo;Park, Jang-Sik;Kim, Hyun-Tae;Son, Kyung-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.2E
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    • pp.36-42
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    • 2006
  • In this paper, a novel post processing using Wiener filtering technique is proposed to p rm further interference reduction in FDICA. Using the proposed method, the target signal components are remained with little attenuation while the interference components are drastically suppressed. The results of experiments show that the proposed method achieves a reduction of the residual crosstalk. Compared to the NLMS method, the proposed method has slightly better separation performance in SIR, and even requires much less computational complexity.

Audio signal separation Algorithm Implementation based PCA (PCA 기반 오디오 신호 분리 알고리즘 구현)

  • Jeon, Jae-Hyeon;Jo, Du-ri;Jeong, Je-chang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2013.11a
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    • pp.151-154
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    • 2013
  • 다수의 음원이 특정한 공간에 산재하고 있을 때, 그 중 특정 음원에 주목하면 다른 음원과 분리되어 특정 음원만 들리는 현상을 칵테일파티 현상이라고 한다. 심리적인 이 현상에 영감을 받아 음원을 분리하는 알고리즘이 만들어졌다. 이런 음원 분리방법을 Blind Source Separation(BSS) 이라고 하는데, 여러 신호가 섞이는 과정을 모르는 상태에서 음원을 분리한다는 뜻에서 Blind Source Separation 이라고 한다. BSS에 사용되는 알고리즘으로 주로 PCA, ICA이 있다. PCA는 2차원의 경우를, ICA는 그 이상의 고차원의 통계적 특성을 이용한다. 이에 본 논문은 PCA를 이용하여 두 음원을 분리하는 알고리즘을 구현하는데 역점을 두었다. PCA는 주로 음원보다는 이미지 신호 처리에 초점이 맞추어져 있지만, 음원 분리에 있어서도 충분한 성능을 보여주므로, ICA를 이용한 음원 분리 알고리즘과의 비교를 통하여 장, 단점을 알아보고 추후 PCA의 응용 가능성을 알아보았다.

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Identification of fault signal for rotating machinery diagnosis using Blind Source Separation (BSS) (BSS를 이용한 회전 기계 진단 신호 분석)

  • Seo, Jong-Soo;Lee, Jeong-Hak;J. K. Hammond
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.839-845
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    • 2003
  • This paper introduces multichannel blind source separation (BSS) and multichannel blind deconvolution (MBD) based on higher order statistics of signals from convolutive mixtures. In particular, we are concerned with the case that the number of inputs is the same as the number of outputs. Simulations for two input two output cases are carried out and their performances are assessed. One of the major applications of those sequential algorithms (BSS and MBD) is demonstrated through the fault signal detection from only a single measurement of rotating machine, which offers a certain degree of practicability in the engineering field such as machine health monitoring or condition monitoring.

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A Note on the Earthquake Double Counting (지진의 이중산입에 대한 소고(小考))

  • Noh, Myunghyun
    • Journal of the Earthquake Engineering Society of Korea
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    • v.27 no.3
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    • pp.157-162
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    • 2023
  • As a result of active geological investigation of faults in Korea, many Quaternary faults have been identified and some of them were judged to have potential to generate earthquakes. Those faults need to be considered as additional seismic sources in the seismic hazard analysis. When a fault is introduced as a new source, the earthquakes generated by the fault should be removed from the area sources that include any part of the fault, to avoid double counting. In practice, however, double counting cannot completely be avoided as the complete separation of the fault-generated earthquakes from the area sources is impossible due to uncertainties related to the earthquake location, subsurface structures of faults, etc. When a new fault source is introduced, the only constraint is the invariance of earthquake frequency. The maximum earthquake and the Richter-b value should also be subject to change, but there are no competent approaches to estimate the change due to incomplete separation of earthquakes. To gain insight into the effect of a new fault source, an example calculation of the seismic hazard were carried out. The example calculation shows that addition of a new fault source centers seismic hazard around the fault source.

Spectrum Sensing for Cognitive Radio Networks Based on Blind Source Separation

  • Ivrigh, Siavash Sadeghi;Sadough, Seyed Mohammad-Sajad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.4
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    • pp.613-631
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    • 2013
  • Cognitive radio (CR) is proposed as a key solution to improve spectral efficiency and overcome the spectrum scarcity. Spectrum sensing is an important task in each CR system with the aim of identifying the spectrum holes and using them for secondary user's (SU) communications. Several conventional methods for spectrum sensing have been proposed such as energy detection, matched filter detection, etc. However, the main limitation of these classical methods is that the CR network is not able to communicate with its own base station during the spectrum sensing period and thus a fraction of the available primary frame cannot be exploited for data transmission. The other limitation in conventional methods is that the SU data frames should be synchronized with the primary network data frames. To overcome the above limitations, here, we propose a spectrum sensing technique based on blind source separation (BSS) that does not need time synchronization between the primary network and the CR. Moreover, by using the proposed technique, the SU can maintain its transmission with the base station even during spectrum sensing and thus higher rates are achieved by the CR network. Simulation results indicate that the proposed method outperforms the accuracy of conventional BSS-based spectrum sensing techniques.

An Improved Multiplicative Updating Algorithm for Nonnegative Independent Component Analysis

  • Li, Hui;Shen, Yue-Hong;Wang, Jian-Gong
    • ETRI Journal
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    • v.35 no.2
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    • pp.193-199
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    • 2013
  • This paper addresses nonnegative independent component analysis (NICA), with the aim to realize the blind separation of nonnegative well-grounded independent source signals, which arises in many practical applications but is hardly ever explored. Recently, Bertrand and Moonen presented a multiplicative NICA (M-NICA) algorithm using multiplicative update and subspace projection. Based on the principle of the mutual correlation minimization, we propose another novel cost function to evaluate the diagonalization level of the correlation matrix, and apply the multiplicative exponentiated gradient (EG) descent update to it to maintain nonnegativity. An efficient approach referred to as the EG-NICA algorithm is derived and its validity is confirmed by numerous simulations conducted on different types of source signals. Results show that the separation performance of the proposed EG-NICA algorithm is superior to that of the previous M-NICA algorithm, with a better unmixing accuracy. In addition, its convergence speed is adjustable by an appropriate user-defined learning rate.

A BUSSGANG-TYPE ALGORITHM FOR BLIND SIGNAL SEPARATION

  • Choi, Seung-Jin;Lyu, Young-Ki
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.1191-1194
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    • 1998
  • This paper presents a new computationally efficient adaptive algorithm for blind signal separation, which is able to recover the narrowband source signals in the presence of cochannel interference without a prior knowledge of array manifold. We derive a new blind signal separation algorithm using the Natural gradient 〔1〕from an information-theoretic approach. The resulting algorithm has the Bussgang property which has been widely used in blind equalization 〔12〕. Extensive computer simulation results comfirm the validity and high performance of the proposed algorithm.

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A New Formulation of Multichannel Blind Deconvolution: Its Properties and Modifications for Speech Separation

  • Nam, Seung-Hyon;Jee, In-Nho
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.4E
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    • pp.148-153
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    • 2006
  • A new normalized MBD algorithm is presented for nonstationary convolutive mixtures and its properties/modifications are discussed in details. The proposed algorithm normalizes the signal spectrum in the frequency domain to provide faster stable convergence and improved separation without whitening effect. Modifications such as nonholonomic constraints and off-diagonal learning to the proposed algorithm are also discussed. Simulation results using a real-world recording confirm superior performanceof the proposed algorithm and its usefulness in real world applications.

A Frequency-Domain Normalized MBD Algorithm with Unidirectional Filters for Blind Speech Separation

  • Kim Hye-Jin;Nam Seung-Hyon
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.2E
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    • pp.54-60
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    • 2005
  • A new multichannel blind deconvolution algorithm is proposed for speech mixtures. It employs unidirectional filters and normalization of gradient terms in the frequency domain. The proposed algorithm is shown to be approximately nonholonomic. Thus it provides improved convergence and separation performances without whitening effect for nonstationary sources such as speech and audio signals. Simulations using real world recordings confirm superior performances over existing algorithms and its usefulness for real applications.

Properties of microlensing events of wide-separation planets with a moon

  • Chung, Sun-Ju;Ryu, Yoon-Hyun
    • The Bulletin of The Korean Astronomical Society
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    • v.40 no.2
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    • pp.57.4-58
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    • 2015
  • Thanks to high cadence monitoring and high photometric accuracy of Korea Microlensing Telescope Network (KMTNet), we expect the detection of many events caused by wide-separation planets and free-floating planets, which is not easy due to the short event duration. Thus, it is important to understand wide-separation planetary lensing events. Several studies on the wide-separation events have been reported, but events caused by wide-separation planetary systems with a moon have not yet been studied. In this paper, we study the properties of events caused by planetary systems where wide-separation planets host a moon. We also study the effect of a finite background source star on the moon feature in the wide planetary-lensing events.

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