• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.924-932
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• 2012

Decomposition of a stereo signal into the primary and ambient components is a key step to the stereo upmix and it is often based on the principal component analysis (PCA). However, major shortcoming of the PCA-based method is that accuracy of the decomposed components is dependent on both the primary-to-ambient power ratio (PAR) and the panning angle. Previously, a modified PCA was suggested to solve the PAR-dependent problem. However, its performance is still dependent on the panning angle of the primary signal. In this paper, we proposed a new PCA-based primary-ambient decomposition algorithm whose performance is not affected by the PAR as well as the panning angle. The proposed algorithm finds scale factors based on a criterion that is set to preserve the powers of the mixed components, so that the original primary and ambient powers are correctly retrieved. Simulation results are presented to show the effectiveness of the proposed algorithm.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.144-154
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• 1999

The binomial sequences are family of orthogonal sequences that can be generated with remarkable simplicity-no multiplications are necessary. This paper introduces a class of non-recursive multidimensional filters for frequency-selective image processing without multiplication operations. The magnitude responses are narrow-band. approximately gaussian-shaped with center frequencies which can be positioned to yield low-pass. band-pass. or high-pass filtering. Algorithms for the efficient implementation of these filters in software or in hardware are described. Also. we show that the binomial QMFs are the maximally flat magnitude square Perfect Reconstruction paraunitary filters with good compression capability and these are shown to be wavelet filters as well. In wavelet transform the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal direction and maintains constant the number of pixels required to describe the images. An efficient perfect reconstruction binomial QMF-Wavelet signal decomposition structure is proposed. The technique provides a set of filter solutions with very good amplitude responses and band split. The proposed binomial QMF-filter structure is efficient, simple to implement on VLSl. and suitable for multi-resolution signal decomposition and coding applications.

• Journal of the Korean Magnetics Society
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• v.18 no.6
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• pp.221-224
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• 2008

This paper describes the equivalent dipole modeling method utilizing a singular value decomposition technique from analysis data by the FNREMUS Detailled Modeller software based on BEM which can predict the underwater electric field signal due to a galvanic corrosion phenomenon on a naval vessel. The proposed dipole modeling method was successfully verified in good agreement with predicted BEM data at 30 m depths through the comparison of average differences. The proposed dipole modelling method can be effectively used in the prediction and analysis of static electric field signature distributions generated from a naval vessel at any different depths.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.123-130
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• 2022

During the past decades, detection of gear defects remains as a major problem, especially when the gears are subject to non-stationary phenomena. The idea of this paper is to mixture a multilevel wavelet transform with a fast EMD decomposition in order to early detect gear defects. The sensitivity of a kurtosis is used as an indicator of gears defect burn. When the gear is damaged, the appearance of a crack on the gear tooth disrupts the signal. This is due to the presence of periodic pulses. Nevertheless, the existence of background noise induced by the random excitation can have an impact on the values of these temporal indicators. The denoising of these signals by multilevel wavelet transform improves the sensitivity of these indicators and increases the reliability of the investigation. Finally, a defect diagnosis result can be obtained after the fast transformation of the EMD. The proposed approach consists in applying a multi-resolution wavelet analysis with variable decomposition levels related to the severity of gear faults, then a fast EMD is used to early detect faults. The proposed mixed methods are evaluated on vibratory signals from the test bench, CETIM. The obtained results have shown the occurrence of a teeth defect on gear on the 5th and 8th day. This result agrees with the report of the appraisal made on this gear system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.275-280
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• 2015

In this paper, we studied for modified MUSIC algorithm of direction of arrival (DOA)estimation. Modified MUSIC algorithm search optimal covariance matrix using singular value decomposition and Bayes method, and desired signals are estimated by updating weight. In order to estimation of desired signals, we used sub spatial method of MUSIC algorithm. General MUSIC algorithm can estimate a desired signal in case of non-correlation signal. But, general MUSIC algorithm in case of correlation signal can not estimate a desired signals and resolution is decreased. Though simulation in case of correlation signal, we analyze to compare proposed MUSIC algorithm with general MUSIC algorithm.

• ETRI Journal
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• v.41 no.3
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• pp.316-325
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• 2019

Accurate suppressive jamming is a prominent problem faced by radar equipment. It is difficult to solve signal detection problems for extremely low signal to noise ratios using traditional signal processing methods. In this study, a joint sensing dictionary based compressed sensing and adaptive iterative optimization algorithm is proposed to counter suppressive jamming in information domain. Prior information of the linear frequency modulation (LFM) and suppressive jamming signals are fully used by constructing a joint sensing dictionary. The jamming sensing dictionary is further adaptively optimized to perfectly match actual jamming signals. Finally, through the precise reconstruction of the jamming signal, high detection precision of the original LFM signal is realized. The construction of sensing dictionary adopts the Pei type fast fractional Fourier decomposition method, which serves as an efficient basis for the LFM signal. The proposed adaptive iterative optimization algorithm can solve grid mismatch problems brought on by undetermined signals and quickly achieve higher detection precision. The simulation results clearly show the effectiveness of the method.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1E
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• pp.31-39
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• 2004

Backscattered underwater signals from multiple scatterers contain information regarding resolvable spatial distribution of scatterers. This experimental study describes the spectral characteristics of backscattered signal from multiple scatterers, which are regularly or randomly spaced, in terms of their amplitude and phase and a proper signal analysis that will eventually provide scatterer spacing estimation. Air-filled tubes suspended in water, steel balls and plastic tubes buried in the sediment are the multiple scatterers. The cepstrum and the spectral autocorrelation (SAC) methods were used to estimate the scatterer spacing from the backscattered signals. It was found that the SAC method could be improved by employing singular value decomposition (SVD) to extract the effective rank for the spectral components. Unlike the conventional method of estimating the density of scatterers within the insonified volume of water, this type of estimation method would provide better understanding of the spatial distribution of scatterers in the ocean.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.164-173
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• 1996

This paper presents an alternative technique for DOA (direction-of-arrival) estimation. For generating a weight vector orthogonal to the signal subspace, a modified version of MES (minimum eigenvalue searching ) method is introduced. The performance of the proposed technique is compared to that of the conventional ED (eigen decomposition) method in terms of angle resolution for a number of snapshots during agiven observation period as well as various SNR's. In addition, the superiority of the suggested technique is shown, by analyzing the required computational load of the proposed MES and conventional ED method. A novel procedure of simplifying the MES proposed in [1] is presented on that purpose. Another advnatage of the proposed technique is that it is performed independently of the detection of the number of signal components, which makes it possible to estimate the DOA's of clusters consisting of infinite number of inseparable signal components.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.84-92
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• 2001

In this papers, we proposed the new method in order to diagnosis aging state of transformers. For wavelet transform, Daubechies filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion skewness, kurtosis) about each acoustic emission signal. Also, these coefficients are used to identify normal and fault signal of internal partial discharge in transformer. As improved method for classification use neural network. Extracted statistical parameters are input into an back-propagation neural network. The number of neurons of hidden layer are obtained through Result of Cross-Validation. The network, after training, can decide whether the test signal is early aging state, alst aging state or normal state. In quantity analysis, capability of proposed method is superior to compared that of classical method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1435-1438
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• 2005

In hands-free telephone systems, the received speech signal is fed back to the microphone and constitutes the so-called echo. To cancel the effect of this time-varying echo path, it is necessary to device an adaptive filter between the receiving and the transmitting ends. For a typical FIR realization, the length of the fullband adaptive filter results in high computational complexity and low convergence rate. Consequently, subband adaptive filtering schemes have been proposed to improve the performance. In this work, we use deterministic approach to analyze the relationship between fullband and subband adaptive filtering structures. With block adaptive filtering structure as an intermediate stage, the analysis is divided into two parts. First, to avoid aliasing, it is found that the matrix of block adaptive filters is in the form of pseudocirculant, and the elements of this matrix are the polyphase components of the fullband adaptive filter. Second, to transmit the near-end voice signal faithfully, the analysis and the synthesis filter banks in the subband adaptive filtering structure must form a perfect reconstruction pair. Using polyphase representation, the relationship between the block and the subband adaptive filters is derived.