• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.7
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• pp.491-499
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• 2018

The conventional calibration method for a noise figure analyzer is to use a noise source. This method is accompanied by a significant irregular ripple in the measurement results, because it does not consider the mismatch of the noise source and noise figure analyzer during calibration. A novel calibration method of the noise figure analyzer is proposed that considers the mismatch between the noise power and noise figure analyzer. A novel noise correlation matrix measurement technique using this method is also proposed. The method determines the noise correlation matrix and the gain of the uncorrected noise figure analyzer using uncorrected noise powers. Then, having determined the gain and noise correlation matrix, the effects of noise figure analyzers were corrected in the measurement results of the noise correlation matrix for the device under test (DUT). Through the proposed method, the measured noise parameters of a DUT showed the same degree of irregular ripples as the result of using the relative noise ratio.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.430-437
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• 2016

In general, noise measurement results show larger random ripple than those of the network analyzer. The reason for the lager random ripple of the noise measurements is considered that the general noise measurements uses absolute measured noise powers, while the network analyzer measures using a ratio of the measured powers. In this paper, a novel measurement method of noise correlation matrix using relative noise ratios is proposed. Proposed method measures the five noise powers of DUT for the five input impedance variations and the four relative noise ratios are formed using the five measured noise powers. The four noise ratios are used to compute the noise correlation matrix and noise parameters. The resulting noise parameters for a 0.5 dB attenuator show good agreements with theoretical values calculated by S-parameters. Also, the noise parameters of an active DUT with a noise figure of less than 1 dB are measured and the measured results show a small random ripple as expected and their values are physically acceptable. In conclusion, the proposed method can be applied to the noise parameter measurements for DUT with a noise figure below 1 dB.

• Bulletin of the Korean Chemical Society
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• v.24 no.9
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• pp.1345-1350
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• 2003

Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.166-171
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• 2022

In this paper, we propose an algorithm to improve DoA(direction of arrival) estimation performance of the subspace-based method by generating high robustness correlation matrix of the signals incident on the uniformly linear array antenna. The existing subspace-based DoA estimation method estimates the DoA by obtaining a correlation matrix and dividing it into a signal subspace and a noise subspace. However, the component of the correlation matrix obtained from the low SNR and small number of snapshots inaccurately estimates the signal subspace due to the noise component of the antenna, thereby degrading the DoA estimation performance. Therefore a robust correlation matrix is generated by arranging virtual signal vectors obtained from the existing correlation matrix in a sliding manner. As a result of simulation using MUSIC and ESPRIT, which are representative subspace-based methods,, the computational complexity increased by less than 2.5% compared to the existing correlation matrix, but both MUSIC and ESPRIT based on RMSE 1° showed superior DoA estimation performance with an SNR of 3dB or more.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.490-496
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• 2020

We present a method to improve the performance of the multi-channel Wiener filter in noisy environment. To build subspace-based multi-channel Wiener filter, in the case of single target source, the target speech component can be effectively estimated in the principal subspace of speech correlation matrix. The speech correlation matrix can be estimated by subtracting noise correlation matrix from signal correlation matrix based on the assumption that the cross-correlation between speech and interfering noise is negligible compared with speech correlation. However, this assumption is not valid in the presence of strong interfering noise and significant error can be induced in the principal subspace accordingly. In this paper, we propose to adjust the principal subspace vector using speech presence probability and the steering vector for the desired speech source. The multi-channel speech presence probability is derived in the principal subspace and applied to adjust the principal subspace vector. Simulation results show that the proposed method improves the performance of multi-channel Wiener filter in noisy environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.04a
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• pp.16-21
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• 1994

For the systems such as ANC(Active Noise Control) systems having auxiliary path after FIR type adaptive filter, Filtered-X LMS algorithm is effective. However behaviors of this algorithm has not been fully understood. The convergence property of this algorithm depends on not only cross correlation matrix between the filtered signals through model and real auxiliary path state solution of weight vector in Filtered-X LMS algorithm is investigated for under-determined case, over-determined case, and nonsingular case. Also, the convergence speed in case of two tone noise is investigated based on the eigenvalue spread of cross correlation matrix.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.134-140
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• 1994

In this paper, an algorithm of CBAM(Combination Bidirectional Associative Memory) model proposes, analyzes and tests CBAM model `s performancess by simulating with recalls and recognitions of patterns. In learning-procedure each correlation matrix of training patterns is obtained. As each correlation matrix's some elements correspond to juxtaposition, all correlation matrices are merged into one matrix (Combination Correlation Matrix, CCM). In recall-procedure, CCM is decomposed into a number of correlation matrices by spiliting its elements into the number of elements corresponding to all training patterns. Recalled patterns are obtained by multiplying input pattern with all correlation matrices and selecting a pattern which has the smallest value of energy function. By using a CBAM model, we have some advantages. First, all pattern having less than 20% of noise can be recalled. Second, memory capacity of CBAM model, can be further increased to include English alphabets or patterns. Third, learning time of CBAM model can be reduced greatly because of operation to make CCM.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.48-59
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• 2000

Eigendecomposition based direction-of-arrival(DOA) estimation algorithm such as MUSIC(multiple signal classification) is known to perform well and provide high resolution in white noise environment. However, its performance degrades severely when the noise process is not white. In this paper we consider the DOA estimation problem in a colored noise environment as a problem of extracting periodic signals from noise, and we take the problem to the wavelet domain. Covariance matrix of multiscale components which are obtained by taking wavelet decomposition on the noise has a special structure which can be approximated with a banded sparse matrix. Compared with noise the correlation between multiscale components of narrowband signal decays slowly, hence the covariance matrix does not have a banded structure. Based on this fact we propose a DOA estimation algorithm that transforms the covariance matrix into wavelet domain and removes noise components located in specific bands. Simulations have been carried out to analyze the proposed algorithm in colored noise processes with various correlation properties.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.253-259
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• 2002

The rigid body characteristics (value of mass, Position of center of mass, moments and products of inertia) of mechanical systems can be identified from FRF data or vibration spectra of rigid body motion. Therefore the accuracy of rigid body characteristics is connected directly with the accuracy of measured data for rigid body motions. In this paper, a method of improving accuracy of measurement of rigid body motion is presented. Applying rigid body theory, ail translational and rotational displacements at a tentative point on the rigid body are calculated using the measured translational displacements for several points and transfer matrix. Then the estimated displacements for the identical points are calculated using the 6 displacements of the tentative Point and transfer matrix. By using correlation coefficient between measured and estimated displacements, we can detect the existence of errors that are contained in a certain measured displacement. Consequently, the improved rigid body motion with respect to a tentative point can be obtained by eliminating the contaminated data.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.343-345
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• 2005

In the study, the noise involved on the active circuit is identified using correlation function. In order to figure out the unknown location of noise source, signals from each sections in the system are collected and the location is identified by a concept called "Noise Source SUI-face". Experiment is conducted to confirm the validity of the proposed method. Also a method to reduce and control the noise in the system signal by using Matrix Pencil Method is introduced. Experiment is attempted to prove that the total noise of system can be reduced by controlling the external noise.