• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.403-408
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• 2008

In this paper, the high efficiency and linearity Doherty power amplifier using DGS and adaptive bias technique has been designed and realized for 2.3GHz WiBro applications. The Doherty amplifier has been implemented us-ing silicon MRF 281 LDMOS FET. The RF performances of the Doherty power amplifier (a combination of a class AB carrier amplifier and a bias-tuned class C peaking amplifier) have been compared with those of a class AB amplifier alone, and conventional Doherty amplifier. The Maximum PAE of designed Doherty power amplifier with DGS and adaptive bias technique has been 36.6% at 34.01dBm output power. The proposed Doherty power amplifier showed an improvement 1dB at output power and 7.6% PAE than a class AB amplifier alone.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.501-506
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• 2010

The proposal set out in this paper, is the Adaptive-MCM(Modulation, Coding and MIMO) system, which results from the combination of adaptive modulation and coding (AMC) and multiple input multiple output (MIMO) schemes. The performance of this system is analyzed through computer simulation. By using the MIMO scheme adaptively as well, the proposed Adaptive-MCM system, presents a better improvement of data rate and error performance compared to the AMC system. The throughput performance of the Adaptive-MCM system is analyzed and compared with the throughput performance of Non-Adaptive-MCM Systems. As a result of the simulation, we can infer that, at a fixed MCM level, there is an improvement of the trade-off between secure Signal to Noise Ratio (SNR) and a high data rate. Consequently, this trade-off improvement results in a better average data rate.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1521-1530
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• 2004

In this paper, we present effective quantization noise reduction algorithm using signal adaptive filter and linear combination between blocks in multimedia system. In the proposed method, all of the blocks are classified into low frequency blocks, high frequency blocks, and midrange blocks according to DCT coefficients. Ringing artifacts are shown in high frequency blocks. So ringing artifact reduction algorithm is performed in high frequency blocks using a signal adaptive filter. And the blocking artifact reduction is performed by replacing the pixel value of blocky blocks using linear combination between blocky block and remote unblocky block. The simulation results shows better performance in respective of the subjective and objective image quality than the conventional method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.1-9
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• 1996

In this paper, a parameter identification method for a discrete-time linear system using multi-layer neural network is proposed. The parameters are identified with the combination of weights and the output of neuraons of a neural network, which can be used for a linear and a nonlinear controller. An adaptive output tracking architecture is designed for the linear controller. And, the nonlinear controller. A sliding mode control law is applied to the stabilizing the nonlinear controller such that output errors can be reduced. The effectiveness of the proposed control scheme is illustrated through simulations.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.57-61
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.192-196
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.927-933
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Proceedings of the IEEK Conference
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• summer
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• pp.348-353
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Journal of Power Electronics
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• v.13 no.1
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• pp.122-138
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• 2013

Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm's weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm's weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.