• Title/Summary/Keyword: Separation Algorithm

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A Method of Sound Segmentation in Time-Frequency Domain Using Peaks and Valleys in Spectrogram for Speech Separation (음성 분리를 위한 스펙트로그램의 마루와 골을 이용한 시간-주파수 공간에서 소리 분할 기법)

  • Lim, Sung-Kil;Lee, Hyon-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.8
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    • pp.418-426
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    • 2008
  • In this paper, we propose an algorithm for the frequency channel segmentation using peaks and valleys in spectrogram. The frequency channel segments means that local groups of channels in frequency domain that could be arisen from the same sound source. The proposed algorithm is based on the smoothed spectrum of the input sound. Peaks and valleys in the smoothed spectrum are used to determine centers and boundaries of segments, respectively. To evaluate a suitableness of the proposed segmentation algorithm before that the grouping stage is applied, we compare the synthesized results using ideal mask with that of proposed algorithm. Simulations are performed with mixed speech signals with narrow band noises, wide band noises and other speech signals.

Hybrid ICA of Fixed-Point Algorithm and Robust Algorithm Using Adaptive Adaptation of Temporal Correlation (고정점 알고리즘과 시간적 상관성의 적응조정 견실 알고리즘을 조합한 독립성분분석)

  • Cho, Yong-Hyun;Oh, Jeung-Eun
    • The KIPS Transactions:PartB
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    • v.11B no.2
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    • pp.199-206
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    • 2004
  • This paper proposes a hybrid independent component analysis(ICA) of fixed-point(FP) algorithm and robust algorithm. The FP algorithm is applied for improving the analysis speed and performance, and the robust algorithm is applied for preventing performance degradations by means of very small kurtosis and temporal correlations between components. And the adaptive adaptation of temporal correlations has been proposed for solving limits of the conventional robust algorithm dependent on the maximum time delay. The proposed ICA has been applied to the problems for separating the 4-mixed signals of 500 samples and 10-mixed images of $512\times512$pixels, respectively. The experimental results show that the proposed ICA has a characteristics of adaptively adapting the maximum time delay, and has a superior separation performances(speed, rate) to conventional FP-ICA and hybrid ICA of heuristic correlation. Especially, the proposed ICA gives the larger degree of improvement as the problem size increases.

Independent Component Analysis Based on Neural Networks Using Hybrid Fixed-Point Algorithm (조합형 고정점 알고리즘에 의한 신경망 기반 독립성분분석)

  • Cho, Yong-Hyun
    • The KIPS Transactions:PartB
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    • v.9B no.5
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    • pp.643-652
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    • 2002
  • This paper proposes an efficient hybrid fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on secant method and momentum for ICA. Secant method is applied to improve the separation performance by simplifying the computation process for estimating the root of objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation if the process of converging to the optimal solution. It can simultaneously achieve a superior properties of the secant method and the momentum. The proposed algorithm has been applied to the composite fingerprints and the images generated by random mixing matrix in the 8 fingerprints of $256\times{256}$-pixel and the 10 images of $512\times{512}$-pixel, respectively. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. Especially, the secant FP algorithm can be solved the separating performances depending on initial points settings and the nonrealistic learning time for separating the large size images by using the Newton FP algorithm.

Feature Selection for Multi-Class Genre Classification using Gaussian Mixture Model (Gaussian Mixture Model을 이용한 다중 범주 분류를 위한 특징벡터 선택 알고리즘)

  • Moon, Sun-Kuk;Choi, Tack-Sung;Park, Young-Cheol;Youn, Dae-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.10C
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    • pp.965-974
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    • 2007
  • In this paper, we proposed the feature selection algorithm for multi-class genre classification. In our proposed algorithm, we developed GMM separation score based on Gaussian mixture model for measuring separability between two genres. Additionally, we improved feature subset selection algorithm based on sequential forward selection for multi-class genre classification. Instead of setting criterion as entire genre separability measures, we set criterion as worst genre separability measure for each sequential selection step. In order to assess the performance proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigate classification performance by GMM classifier and k-NN classifier for selected features using conventional algorithm and proposed algorithm. Proposed algorithm showed improved performance in classification accuracy up to 10 percent for classification experiments of low dimension feature vector especially.

A Propagated-Mode LISP-DDT Mapping System (전달모드 LISP-DDT 매핑 시스템에 관한 연구)

  • Ro, Soonghwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.12
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    • pp.2211-2217
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    • 2016
  • The Locator/Identifier Separation Protocol (LISP) is a new routing architecture that implements a new semantic for IP addressing. It enables the separation of IP addresses into two new numbering spaces: Endpoint Identifiers (EIDs) and Routing Locators (RLOCs). This approach will solve the issue of rapid growth of the Internet's DFZ (default-free zone). In this paper, we propose an algorithm called the Propagated-Mode Mapping System to improve the map request process of LISP-DDT.

An Efficient Composite Image Separation by Using Independent Component Analysis Based on Neural Networks (신경망 기반 독립성분분석을 이용한 효율적인 복합영상분리)

  • Cho, Yong-Hyun;Park, Yong-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.3
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    • pp.210-218
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    • 2002
  • This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of $512{\times}512-pixel$, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.

Frequency Domain Blind Source Seperation Using Cross-Correlation of Input Signals (입력신호 상호상관을 이용한 주파수 영역 블라인드 음원 분리)

  • Sung Chang Sook;Park Jang Sik;Son Kyung Sik;Park Keun-Soo
    • Journal of Korea Multimedia Society
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    • v.8 no.3
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    • pp.328-335
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    • 2005
  • This paper proposes a frequency domain independent component analysis (ICA) algorithm to separate the mixed speech signals using a multiple microphone array By estimating the delay timings using a input cross-correlation, even in the delayed mixture case, we propose a good initial value setting method which leads to optimal convergence. To reduce the calculation, separation process is performed at frequency domain. The results of simulations confirms the better performances of the proposed algorithm.

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Adaptive IIR filter designed for the separation of scintillation and rain attenuation phenomena

  • Sangaroon, O.;Chutchavong, V.;Anekpongpun, K.;Benjangkaprasert, C.;Sooraksa, P.;Moriya, Y.
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.109.5-109
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    • 2001
  • The separation of scintillation phenomena concurrent with rain attenuation phenomena can be accomplished by filtering. Based on the analysis of satellite signal fading during rain, scintillation and rain attenuation phenomena are examined and extracting from raw data by using adaptive IIR high-pass filter and adaptive IIR low-pass filter. Adaptive IIR filter are designed by using the algorithm of Least Mean p-Power (LMP) Error Criterion which have been modified by Quantizing Gradient technique. This algorithm reduces amount of multiplication computational equal to the length of input data. It is prove here that the convergence speed, variance, bias independence on p values. For this application, p=1 is chosen. The procedure of application ...

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Development of an Automatic Two-Dimensional Mesh Generator using an Inward Offset Boundary Technique

  • Choi, Jin-Woo;Kim, Yohng-Jo
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.2 no.4
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    • pp.61-66
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    • 2003
  • An excellent mesh construction is of Importance in yielding good results of finite element analysis. The new mesh generation algorithm, which offsets boundaries inward, was developed on the basis of a looping method. An user interface technique and automatic splitting lines which both divide a given domain into subdomains manually or automatically, were used. In addition, the separation method has advantages to prevent the large scale of element size and to control numbers of nodes and elements. This new mesh generation algorithm was proved in practice.

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The Remote Control of Mobile Robots on the Web (웹을 이용한 이동로봇의 원격제어)

  • Ok, J.S.;Kang, G.T.;Lee, W.C.
    • Journal of Power System Engineering
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    • v.4 no.4
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    • pp.78-83
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    • 2000
  • It is often necessary to observe the working environment of a robot to control it efficiently in the remote location. The remote sensing data and control commands are transmitted via various media such as radio, microwave, and computer network. The World Wide Web can be used as the infrastructure for teleoperation of mobile robots. In this paper we propose an advanced technique of the remote control of mobile robots on the web. For the real-time control, the image separation algorithm is proposed to transmit the current positions of mobile robots instead of transmitting the full frame image. It is shown by experiments that the proposed algorithm is effective.

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