• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1149-1159
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• 2008

Blind source extraction (BSE) is a special class of blind source separation (BSS) methods, which only extracts one or a subset of the sources at a time. Based on the time delay of the desired signal, a simple but important extraction algorithm (simplified " BC algorithm")was presented by Barros and Cichocki. However, the performance of this method is not satisfying in some cases for which it only carries out the constrained minimization of the mean squared error. To overcome these drawbacks, ICA with reference (ICA-R) based approach, which considers the higher-order statistics of sources, is added as the second stage for further source extraction. Specifically, BC algorithm is exploited to roughly extract the desired signal. Then the extracted signal in the first stage, as the reference signal of ICA-R method, is further used to extract the desired sources as cleanly as possible. Simulations on synthetic data and real-world data show its validity and usefulness.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.13-17
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• 2006

In this paper, we propose an audio extraction method to decrease the influence of the original signal by modifying the watermarking detection system proposed by P. Bassia et al. In the extraction of the watermark, we employ a simple mean filter to remove the influence of the original signal as a preprocessing of extraction and the repetitive insertion of the watermark. As the result of the experiment, for which we used about 20 kinds of actual audio data, we obtain a watermark detection rate of about 95% and a good performance even after the various signal processing attacks.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.609-612
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• 2000

본 논문에서는 음원에 관한 정보가 미지의 상황에서 마이크로폰 어레이를 사용하여 두 음원신호를 분리하는 ,시스템을 제안한다 이 시스템은 두 단계로 구성되어 있으며, 첫 번째 단계에서는 파워가 큰 제 1음원의 DOA(Direction Of Arrival)를 추정하고, AMUSE(Algorithm for Multiple Unknown Signals Extraction)법을 사용한 Blind Deconvolution에 의해 음원신호의 분리를 행한다 두 번째 단계에서는 파워가 낮은 제 2음원의 강조신호를 사용하여 DSA(Delay and Sum Array)법에 의해 제 2음원의 DOA를 추정하고,AMUSE법의 출력신호와 두 음원의 DOA를 이용하여 ANF(Adaptive Notch Filter)를 구성하고, 두 음원신호의 재 분리를 행한다. 그리고, 시뮬레이션을 통해 제안한 방법의 유효성을 검토한 결과 두 음원 신호가 분리 가능한 것이 확인되었다.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.1
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• pp.41-46
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• 2004

This paper proposes a separation of mixed signals by using the robust independent component analysis(RICA) based on neural networks. RICA is based on the temporal correlations and the second order statistics of signal. This method e is applied for improving the analysis rate and speed in which the sources have very small or zero kurtosis. The proposed method has been applied for separating the 10 mixed finger prints of $256{\times}256$-pixel and the 4 mixed images of $512{\times}512$-pixel, respectively. The simulation results show that RICA has the separating rate and speed better than those using the conventional FP algorithm based on Newton method.

• ETRI Journal
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• v.31 no.2
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• pp.193-200
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• 2009

In this paper, we study the performance of subspace-based multiuser detection techniques for multicarrier code-division multiple access (MC-CDMA) systems. We propose an improvement in the PASTd algorithm by cascading it with the classical Gram-Schmidt procedure to orthonormalize the eigenvectors after their sequential extraction. The tracking of signal subspace using this algorithm, which we call OPASTd, has a faster convergence as the eigenvectors are orthonormalized at each discrete time sample. This improved PASTd algorithm is then used to implement the subspace blind adaptive multiuser detection for MC-CDMA. We also show that, for multiuser detection, the complexity of the proposed scheme is lower than that of many other orthogonalization schemes found in the literature. Extensive simulation results are presented and discussed to demonstrate the performance of the proposed scheme.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.807-812
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• 2020

This paper proposes a blind speech source separation algorithm using a microphone to separate only the target speech source signal in an environment in which various speech source signals are mixed. The proposed algorithm is a model of frequency domain representation based on independent component analysis method. Accordingly, for the purpose of verifying the validity of independent component analysis in the frequency domain for two speech sources, the proposed algorithm is executed by changing the type of speech sources to perform speech sources separation to verify the improvement effect. It was clarified from the experimental results by the waveform of this experiment that the two-channel speech source signals can be clearly separated compared to the original waveform. In addition, in this experiments, the proposed algorithm improves the speech source separation performance compared to the existing algorithms, from the experimental results using the target signal to interference energy ratio.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2101-2102
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• 2006

In this paper, a new digital audio watermarking algorithm is presented. The proposed algorithm embeds watermark into audio signal based on human auditory system (HAS). This algorithm is a blind audio watermarking method, which does not require any prior information during watermark extraction process. This algorithm finds watermarking position using time-domain masking effect. First we insert the watermark into wavelet domain, and then we use a back-propagation neural network (BPN) to learn the characteristics of relationship between the watermark and the watermarked audio. Due to the teaming and adaptive capabilities of the BPN, the false recovery of the watermark can be greatly reduced by the trained BPN. Experimental results show that the proposed method has good inaudibility and high robustness to common audio processing attacks.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.179-186
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• 2009

This paper proposes a target speech extraction which restores speech signal of a target speaker form noisy convolutive mixture of speech and an interference source. We assume that the target speaker is known and his/her utterances are available in the training time. Incorporating the additional information extracted from the training utterances into the separation, we combine convolutive blind source separation(CBSS) and non-negative decomposition techniques, e.g., probabilistic latent variable model. The nonnegative decomposition is used to learn a set of bases from the spectrogram of the training utterances, where the bases represent the spectral information corresponding to the target speaker. Based on the learned spectral bases, our method provides two postprocessing steps for CBSS. Channel selection step finds a desirable output channel from CBSS, which dominantly contains the target speech. Reconstruct step recovers the original spectrogram of the target speech from the selected output channel so that the remained interference source and background noise are suppressed. Experimental results show that our method substantially improves the separation results of CBSS and, as a result, successfully recovers the target speech.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3438-3454
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• 2018

In this paper, we propose a robust blind watermarking scheme for high-definition video. In the embedding process, luminance component of each frame is transformed by 2-dimensional fast Fourier transform (2D FFT). A secret key is used to generate a matrix of random numbers for the security of watermark information. The matrix is transformed by inverse steerable pyramid transform (SPT). We embed the watermark into the low and mid-frequency of 2D FFT coefficients with the transformed matrix. In the extraction process, the 2D FFT coefficients of each frame and the transformed matrix are transformed by SPT respectively, to produce two oriented sub-bands. We extract the watermark from each frame by cross-correlating two oriented sub-bands. If a video is degraded by some attacks, the watermarks of frames contain some errors. Thus, we use an ensemble position-based error correcting algorithm to estimate the errors and correct them. The experimental results show that the proposed watermarking algorithm is imperceptible and moreover is robust against various attacks. After embedding 64 bits of watermark into each frame, the average peak signal-to-noise ratio between original frames and embedded frames is 45.7 dB.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.1-8
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• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.