• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.123-128
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• 2017

This paper relates with the Hybrid-SMMA adaptive equalization algorithm that is possible to improve the equalization performance based on adaptive modulus and adaptive stepsize which is propotional to the output power of equalizer in the current SMMA (Sliced Multi Modulus Algorithm). The fixed statistic modulus of transmitted signal is used in current SMMA algorithm in order to generate the error signal for updating the tap coefficient of equalizer. The proposed Hybrid-SMMA based on the adaptive modulus which is propotion to the equalizer output signal power and adaptive stepsize which is fuction of the nonlinearties of error signal. The computer simulation was performed in order to confirm the improved equalization performance of proposed algorithm. As a result of computer simulation, the proposed Hybrid-SMMA has fairly good in every performance than the current SMMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.107-113
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• 2019

This paper proposes the Hybrid-CRMMA adaptive equalization algorithm that is possible to improves the performance of CR-MMA based on adaptive modulus and adaptive stepsize. The 16-QAM nonconstant modulus signal is reduced to 4-QAM constant modulus signal, and the error signal were obtained based on the fixed statistic modulus of transmitted signal. It is possible to improving the currently MMA adaptive equalization performance. The proposed Hybrid-CRMMA composed of adaptive modulus which is propotional to the power of equalizer output and adaptive stepsize which is function of the nonlinearties of error signal, and its improved equalization performance were confirmed by computer simulation. For this purpose, the output signal constellation, the residual isi and maximum distortion and MSE that is for the convergence characteristics, the SER that is meaning the robustness of external noise of algorithm were used. As a result of computer simulation, it was confirmed that the proposed Hybrid-CRMMA has more superior performance in every index compared to currently CR-MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.75-80
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• 2021

This paper relates with the Hybrid-DSE-MMA (Hybrid-Dithered Signed Error-MMA) that is possible to improving the equalization performance by using the adaptive modulus and adaptive stepsize in DSE-MMA adaptive equalizer. The DSE-MMA possible to improve the robustness performance to external noise of SE-MMA by using the sign after adding the dither signal for get the error signal in order to update the tap coefficient. But it has a drawback of performance degradation in convergence speed and residual isi by using the fixed modulus and fixed stepsize. In this paper, it was confirmed that this equalization performance degradation was improved by applying the adaptive modulus and stepsize in DSE-MMA propotional to the output power of equalizer by computer simulation. In order to compare the improved equalization performance to currently DSE-MMA, the recovered signal constellation that is the output of the equalizer, residual isi, Maximum Distortion, MSE and the SER were used as a performance index. As a result of computer simulation, the Hybrid-DSE-MMA improve the equalization performance in every index, but gives slower convergence speed compared to DSE-MMA.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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• pp.61-70
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• 2012

This paper describes terrain-adaptive attitude controller for a hybrid mobile platform which operates in wheel & track mode. The wheel mode of the hybrid mobile platform allows quick driving performance in the flatland, while the track mode provides adaptive movement in the rough ground or stairway. The switching of the platform between two modes is automatically controlled by attitude controller algorithm. In addition, in the track mode, the platform automatically adjusts its attitude angle to overcome the obstacles in front. This paper demonstrates the attitude controller for the aforementioned wheel-track hybrid mobile platform in order to overcome terrain obstacles by using an adaptive method. The driving performance of the hybrid mobile platform has been tested and verified in various surrounding environments in both wheel and track mode. Further, this paper presents the experiments by using the track structure of mobile platform on forming adaptive attitude under various types of obstacles. The practicability and effectiveness of the proposed attitude controller of the platform has been demonstrated in urban building and a test-bed.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3E
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• pp.95-103
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• 2008

In this paper, the new hybrid adaptive Volterra filter was proposed to be applied for compensating the nonlinear distortion of memoryless nonlinear systems with saturation characteristics. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional Volterra filter and proposed hybrid Volterra filter, to be applied for linearizing the memoryless nonlinear system with nonlinear distortion. Also, the simulations results demonstrated that the proposed hybrid filter may have faster convergence speed and better capability of compensating the nonlinear distortion than the conventional Volterra filter.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.145-145
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• 2000

In this paper, we propose a hybrid d-step predictor which is composed of an adaptive predictor and a Kalman predictor. We prove the performance limit of the proposed predictor. Simulation is conducted to examine the performance of the proposed predictor. Simulation results show that the proposed combined predictor is superior to the adaptive predictor and the Kalman predictor. Proposed predictor is used for prediction of gun tip vibration of k1 tank. The result is compared with that of conventional adaptive predictor.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.179-182
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• 2003

This paper proposes an adaptive hybrid genetic algorithm (aHGA) for effectively solving the complex reliability optimization problems. The proposed aHGA uses a loca1 search technique and an adaptive scheme for respectively constructing hybrid algorithm and adaptive ability. For more various comparisons with the proposed adaptive algorithm, other aHGAs with conventional adaptive schemes are considered. These aHGAs are tested and analyzed using two complex reliability optimization problems. Numerical result shows that the proposed aHGA outperforms the other competing aHGAs.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.443-449
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• 2000

The performance of 2-frame PTV(particle tracking velocimetry) system was improved using an adaptive hybrid scheme. The original 2-frame PTV method based on the match probability concept employs global match parameters for the entire flow field. Since this does not reflect fully the detailed local velocity change, it sometimes reduces the recovery rate of velocity vectors and increases the number of erroneous vectors in the region where an extraordinary flow structure exists. In this study, the preliminary FFT-based PIV results are used as an input parameter to determine the local match parameters needed for the 2-frame particle tracking algorithm. A computer simulation using synthetic particle images was carried out to study the performance of the adaptive 2-frame PTV technique. The adaptive hybrid method shows the better performance with increasing the velocity vector recovery rate and decreasing the computation time, compared to the original 2-frame PTV method.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1379-1382
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• 1987

IN ADAPTIVE LINEAR PREDICTION, AN ADAPTIVE CAPABILITY IS BUILT INTO THE PROCESSOR SUCH THAT AS THE IMAGE STATISTICS CHANGE, THE PREDICTION FILTER COEFFICIENTS THEMSELVES CHANGE, PRODUCING A NEW FILTER MORE CLOSELY OPTIMIZED TO THE NEW SET OF IMAGES STATISTICS. THE LMS ALGORITHM MAY BE USED TO ADAPT THE COEFFICIENT OF AN ADAPTIVE PREDICTION FILTER FOR IMAGE SOURCE ENCODING. IN THIS PAPER, TWO CODING SYSTEMS USING DPCM AND LMS ALGORITHMS RESPECTIVELY FOR OBTAINING THE FIRST TRANSFORMED COEFFICIENT IN HYBRID CODING ARE COMPARED.