• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.247-252
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• 2004

In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.158-166
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• 2005

Even though post-processing methods based on projections onto convex sets (POCS) have shown good performance for blocking artifact reduction, it is infeasible to implement POCS for real-time practical applications. This paper proposes DCT domain post-processing method based on POCS. The proposed method shows very similar performance compared to the conventional POCS method, while it reduces tremendously the computational complexity. DCT domain POCS performs the lowpass filtering in the DCT domain, and it removes the inverse DCT and forward DCT modules. Through the investigation of lowpass filtering in the iterative POCS method, we define kth order lowpass filtering which is equivalent to the lowpass filtering in the kth iteration, and the corresponding kth order DCT domain POCS. Simulation results show that the kth order DCT domain POCS without iteration gives very similar performance compared to the conventional POCS with k iterations, while it requires much less computations. Hence the proposed DCT domain POCS method can be used efficiently in the practical post-processing applications with real-time constraints.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.363-368
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• 2004

In this paper, the robustness property of 2nd-order iterative learning control(ILC) method for a class of linear and nonlinear discrete-time dynamic systems is studied. 2nd-order ILC method has the PD-type learning algorithm based on both time-domain performance and iteration-domain performance. It is proved that the 2nd-order ILC method has robustness in the presence of state disturbances, measurement noise and initial state error. In the absence of state disturbances, measurement noise and initialization error, the convergence of the 2nd-order ILC algorithm is guaranteed. A numerical example is given to show the robustness and convergence property according to the learning parameters.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.71-77
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• 1995

In this paper are proposed robust iterative learning control(ILC) algorithms for both linear continuous time-invariant system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.148-154
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• 2010

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen 802.11n for wireless local access network(WLAN) standard are required a large number of computation due to large size of coded block and iteration. Therefore, we presented three kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algorithm. Secondly, we have apply early stop algorithm. This method is reduced number of unnecessary iteration. Third, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and early stop algorithm is reduced more than one iteration and computational complexity of early detected method is about 30% offs in case of check node update, 94% offs in case of check node update compared to conventional scheme.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1117-1120
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• 1999

In this paper, we design the H$\infty$ optimal controller satisfying robust stability and performance in spite of the plant uncertainty for an electro-mechanical actuator system and analyze the controller in frequency domain. H$\infty$ optimal controller K was designed using iteration algorithm suggested by DOYLE. Using the controller in an electro-mechanical actuator system, the joint with very small coupling rigidity coefficient was used to vary the control parameter. The plant unstructured uncertainty was assumed to be a multiplicative type.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.26-32
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• 2014

Single-Carrier Frequency division multiplexing (SC-FDM) has been selected for the uplink transmission technique in 3GPP-LTE since it has an advantage of low peak-to-average power ratio (PAPR) in user's perspective. The receiver typically uses a frequency domain equalizer, which, however, suffers from noise boost and/or residual ISI especially when the channel has deep nulls. In this paper, we propose using turbo equalizer to mitigate such a problem. We provide link level performance comparison and an insight into how many iteration is needed for reasonable performance and complexity.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.163-169
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• 1998

In this paper, we design an optimal model following ${\mu}-$synthesis control system for fuel-injection of diesel engine which has robust performance and satisfactory command tracking performance in spite of uncertainties of the system. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithm with reference model to the optimal determination of the weighting functions that are given by the D-K iteration method which can design ${\mu}-$synthesis controller in the state space. These weighting functions are optimized simultaneously in the search domain which guarantees the robust performance of the system. The ${\mu}-$synthesis control system for fuel-injection designed by the above method has not only the robust performance but also a better command tracking performance than those of the ${\mu}-$synthesis control system designed by trial-and-error method. The effectiveness of this ${\mu}-$synthesis control system for fuel-injection is verified by computer simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.965-972
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• 2005

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen for second generation digital video broadcasting standard, are required a large number of computation due to large size of coded block and iteration. Therefore, we presented two kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algerian. Secondly, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and computational complexity of early detected method is about $50\%$ offs in case of check node update, $99\%$ offs in case of check node update compared to conventional scheme.

• Phonetics and Speech Sciences
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• v.7 no.4
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• pp.17-25
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• 2015

For blind source separation of convolutive mixtures, FDICA(Frequency Domain Independent Component Analysis) algorithms are generally used. Since FDICA algorithm such as Sawada FDICA, IVA(Independent Vector Analysis) works on the frequency bin basis with a natural gradient descent method, it takes much time to converge. In this paper, we propose a new method to improve convergence speed in FDICA algorithm. The proposed method reduces the number of iteration drastically in the process of natural gradient descent method by applying a weighted inner product constraint of unmixing matrix. Experimental results have shown that the proposed method achieved large improvement of convergence speed without degrading the separation performance of the baseline algorithms.