• The Journal of the Acoustical Society of Korea
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• v.16 no.3
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• pp.38-44
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• 1997

In this study, wer derived LMF-Sato, LMSF-Sato complex blind equalization algorithms for complex data. And then, the convergence rates, the convergence characteristics at the steady state and the stability of the proposed LMF and LMSF blind equalization algorithms are compared with those of LMS-Sato blind equalization algorithm. In simulations with 16-QAM data, LMF-Sato and LMSF-Sato algorithms showed better performance comparing with LMS-Sato algorithm generally. When the initial estimation errors of the weights of the equalizer are large, LMF-Sato algorithm showed ill characteristic in stability. However, LMSF-Sato algorithm has good covergence characteristics and preserves robustness.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.215-221
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• 2010

This paper introduces development of location estimation and navigation system of mobile robots using USN and LEGO Mindstorms NXT. Developed system includes location estimation, location and navigation information display and navigation control parts. It used ZigBee based USN which was built with CC2431 chip to locate blind node and implemented fuzzy model to improve ability of calculation of distances from reference nodes and location of mobile robots. This paper proposed combination method of location estimation using USN and encoder which is built in motors of mobile robots. Experimental results showed proposed method is superior to the method which used USN only in location estimation and navigating robots. Developed system can locate current position of mobile robots and monitor information from sensor nodes like temperature, humidity and send control signal to mobile robot to move.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.27-34
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• 2006

In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.450-457
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• 2012

For orthogonal frequency-division multiplexing (OFDM) systems, we propose a blind channel estimation scheme based on non-redundant precoding. In the proposed scheme, a modified covariance matrix is first obtained by dividing the covariance matrix of the received signal vector by the precoding matrix element-by-element. Then, the channel vector is estimated as an eigenvector corresponding to the largest eigenvalue of the modified covariance matrix. The eigenvector can be obtained by power method with low computational complexity instead of the complicated eigenvalue decomposition. We analytically derive a mean square error (MSE) of the proposed channel estimation scheme and show that the analysis result coincides well with the simulation result. Also, simulation results show that the proposed scheme has better MSE and bit error rate (BER) performance than conventional channel estimation schemes.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.202-202
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• 2004

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.17-24
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• 2014

Blind algorithms designed to maximize the probability that constant modulus errors become zero carry out some summation operations for a set of constant modulus errors at an iteration time inducing heavy complexity. For the purpose of reducing this computational burden induced from the summation, a new approach to the estimation of the zero-error probability (ZEP) of constant modulus errors (CME) and its gradient is proposed in this paper. The ZEP of CME at the next iteration time is shown to be calculated recursively based on the currently calculated ZEP of CME. It also is shown that the gradient for the weight update of the algorithm can be obtained by differentiating the ZEP of CME estimated recursively. From the simulation results that the proposed estimation method of ZEP-CME and its gradient produces exactly the same estimation results with a significantly reduced computational complexity as the block-processing method does.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.4
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• pp.365-370
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• 2013

In this paper, we propose robust blind estimators for the frequency offset of orthogonal frequency division multiplexing in non-Gaussian noise environments. We first propose a maximum likelihood (ML) estimator in non-Gaussian noise modeled as a complex isotropic Cauchy process, and then, a simpler estimator based on the ML estimator is proposed. From numerical results, we confirm that the proposed estimators are robust to the non-Gaussian noise and have a better estimation performance over the conventional estimator in non-Gaussian noise environments.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.24-29
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• 2012

The sounds of exhaust emissions of automobiles are independent sound sources which are nothing to do with voices. We have no information for the sources of voices and exhaust sounds. Accordingly, Independent Component Analysis which is one of the Blind Source Separaton methods was used to segregate two source signals from each mixed signals. Maximum Likelyhood Estimation was applied to the signals came through the stereo microphone to segregate the two source signals toward the maximization of independence. Since there is no clue to find whether it is speech signal or not, the coefficients of the slope was calculated by the autocovariances of the signals in frequcency domain. Noise remover for speech signals was implemented by coupling the two algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.1001-1009
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• 2009

In this paper, an efficient blind frequency offset estimation method for radio resource saving in orthogonal frequency division multiplexing (OFDM) systems is proposed. In the proposed method, we obtain two time different received OFDM signal blocks by using the cyclic prefix and define the cost function by using the two OFDM signal blocks. We show that the cost function can be approximately expressed as a closed form cosine function. The approximated cosine function can be obtained from three independent cost function values calculated at three different frequency offsets. In the proposed method, the frequency offset can be estimated by calculating a frequency offset minimizing the approximated cosine function without searching all the frequency offset range. Unlike the conventional methods such as MUSIC method, the accuracy of the proposed method is independent of the searching resolution since the closed form solution exists. The computer simulation shows that the performance of the proposed method is superior to those of the MUSIC and the oversampling method.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.158-163
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• 1992

This paper describes the estimation of the solid friction in mechanical systems by using the extended Kalman filtering techniques. We proposed two stochastic model for the estimation. The one is the 'parametric model' which represents the friction characteristics by an exponential function with unknown parameters. The other is the 'blind model' which does not assume an explicit model but regard the effect of the friction as an unknown input to a known dynamic system. For both models, we give estimation algorithms to generate the filtered estimate and the smoothed estimate with a fixed lag. The filtered estimate can be generated on-line for compensating the solid friction in mechanical systems. Although on-line applications are impossible, the smoothed estimate is more accurate and can be used to grasp precise friction characteristics. Simulation and experimental results arc presented to show the effectiveness of the proposed techniques.