• The Journal of the Acoustical Society of Korea
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• v.20 no.4E
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• pp.39-44
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• 2001

We investigate the numerical instability of linear prediction for discrete harmonic spectra of audio signals. It is identified that the eigenvalue spread is very large when discrete harmonic spectra are confined only in a lower part of the entire signal bandwidth. A simple method that redefines the sampling frequency and associate harmonic frequencies is proposed to improve the numerical stability. Simulation results using real audio signals indicate its superior stabilizing ability and improved accuracy in the discrete spectral estimation for both LP and DAP.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1188-1197
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• 1995

This paper describes an algorithm that reduces computational requirement of the Kalman filter and estimates the signal efficiently. The reference signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be smaller than that in the time domain. In the wavelet transform domain the autocorrelation matrix is nearly diagonal. Therefore, the transformed signal can be decomposed each orthogonal elements. The Kalman filter can be applied to each orthogonal elements and computational requirement is reduced. The possibility of applying the parallel Kalman filter was verified through the theory and simulation. The eigenvalue spread in the wavelet transform domain is smaller 8.35 times than that in the time domain and the computational requirement is reduced from 1.4 times to 2. 93 times than that of the conventional Kalman filter.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.305-316
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• 1994

All physical data in the real world are nonstationary signals that have the time varying statistical characteristics. Although few algorithms suitable to process the nonstationary signals have ever been suggested, these are treated the nonstationary signals under the assumption that the nonstationary signal is a piece-wise stationary signal. Recently, statistical analysis algorithms for the nonstationary signal have concentrated so much interest. In this paper, nonstationary EMG signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be more smaller than that in the time domain. Then the model in the wavelet transform domain and an algorithm to estimate the model parameters are suggested. Also, an test signal generated by a white gaussian noise and the EMG signal are identified, and the algorithm performance is considered in the sense of the mean square error and the evaluation parameters.

• ETRI Journal
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• v.28 no.2
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• pp.155-161
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• 2006

In this paper, we introduce an escalator (ESC) algorithm based on the least squares (LS) criterion. The proposed algorithm is relatively insensitive to the eigenvalue spread ratio (ESR) of an input signal and has a faster convergence speed than the conventional ESC algorithms. This algorithm exploits the fast adaptation ability of least squares methods and the orthogonalization property of the ESC structure. From the simulation results, the proposed algorithm shows superior convergence performance.

• Journal of electromagnetic engineering and science
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• v.4 no.2
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• pp.93-96
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• 2004

In this paper we introduce a new escalator(ESC) structure-based adaptation algorithm. The proposed algorithm is independent of eigenvalues spread ratio(ESR) of channel and has faster convergence speed than that of the conventional ESC algorithms. This algorithm combines the fast adaptation ability of least square methods and the orthogonalization property of the ESC structure. From the simulation results the proposed algorithm shows superior convergence speed and no slowing down of convergence speed when we increase the ESR of the channel.

• Journal of Advanced Navigation Technology
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• v.3 no.2
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• pp.167-173
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• 1999

This paper showed the convergence rate and the performance of interference cancellation using Applebaum and DMI algorithms in adaptive sidelobe canceller. Applebaum algorithm is used widely due to simplicity but it has a slow convergence rate and the problem of eigenvalue spread. DMI algorithm converges rapidly but has computational load and hardware complexity. We compared the performance and complexity using Applebaum and DMI algorithms in Adaptive SLC that requires rapid convergence rate and the performance and conclude that DMI algorithm is more efficient for adaptive SLC.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.60-67
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• 2000

When the eigenvalues of the input covariance matrix of an array system spread by orders of magnitude, conventional adaptive arrays can't remove all the interference signals effectively In this paper, an Applebaum array adopting an adaptive gain controller (AGC) in the feedback loop of the array is proposed When eigenvalue spreaded interferences are incident to an array, a high power interference is removed easily in several iterations while a relative low power interference which is a cause of eigenvalue spread is still remained In the array output After some initial iterations, the proposed array increases the correlation between the low power interference and the array output by amplifying the output signal of the array As a result, the weights vector adapts to the direction of the low power interference as well as that of the high power interference Computer simulation results show that the proposed array gives high output signal to interference plus noise ratio (SINR) and a fast convergence speed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.10
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• pp.989-997
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• 2002

This paper presents a new technique that enhances the performance of the smart antenna system especially in signal environments of wide angular spread by adopting a weight vector obtained from two eigenvectors of theautocovariance matrix of the received data. While the conventional beamformingtechnique employs only one eigenvector corresponding to the largest eigenvalue, the proposed algorithm uses two eigenvectors corresponding to the largest and second largest eigenvalue in such a way that it can be robust enough to the signal environments of wide angular spread. An efficient adaptive procedure is shown to verify that the optimal weight vector consisting of the two eigenvectors is obtained with a reasonable complexity(3.5$N_2$+ 12N) and accuracy. it is also shown in this paper that the numerical results obtained from the proposed adaptive procedure well agree with those obtained from a commercial tool computing the eigen-function of MATLABTM.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1920-1923
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• 2002

This paper proposes an impulse response shortening algorithm applicable to decision feedback equalization of single carrier wideband signal. When he impulse response shortening methods for narrowband signaling are applied to single carrier wideband signals, they result in noise enhancement problem, significantly deterioriting the receiver performance. This problem can be alleviated by educing the eigenvalue spread ratio of the impulse response, which can be achieved by adding additive white noise with small variance to the impulse response of the channel. The performance of the proposed scheme is verified by computer simulation.

• ETRI Journal
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• v.40 no.2
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• pp.197-206
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• 2018

Multiple-input multiple-output (MIMO) systems offer significant enhancements in terms of their data rate and channel capacity compared to traditional systems. However, correlation degrades the system performance and imposes practical limits on the number of antennas that can be incorporated into portable wireless devices. The use of switched parasitic antennas (SPAs) is a possible solution, especially where it is difficult to obtain sufficient signal decorrelation by conventional means. The covariance matrix represents the correlation present in the propagation channel, and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the "water-pouring algorithm" to modify the covariance matrix, the channel capacity is significantly improved compared to traditional systems, which spread transmit power uniformly across all the antennas. A condition number is also proposed as a selection metric to select the optimal pattern configuration for MIMO-SPAs.