• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.120-130
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• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.70-76
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• 2012

The independent component analysis (ICA) technique is a source identification method that uses statistical independence to separate source signals from measured signals. It has been successfully applied to various fields such as medical care and communication. In this study, the ICA technique was adopted to analyze the vibration source contribution of plate structures. The theory of the ICA technique is introduced and the procedure of the vibration source contribution analysis based on the ICA technique is proposed. To investigate the applicability of the proposed method to plate structures, numerical examples are presented for a rectangular plate under harmonic force excitations. The results show that the proposed method could become an effective tool for the vibration source contribution analysis of a plate structure.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.59-65
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• 2012

Hot pepper can be easily faded or discolored in drying process, so we need to use the sorting technique to improve the quality for dried hot pepper. Independent Component Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to get a concentration image of the most important component which plays a role in the dried pepper. This concentration image is different from the binary image and it reflects the characteristics of major components, so that we know the distribution and quality of the component and how to sort the dried pepper. Also, the size of the concentration image can tell the relation with capsaicinoids which make hot taste. We propose a sorting method of the dried hot pepper that is faded or discolored and lacked a major component likes capsaicin in drying process using ICA concentration image.