• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.70-82
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• 1993

In this paper, employing the 3-dimensional discrete cosine transform (DCT) for the utilization of the temporal correlation, an adaptive motion sequence coding technique is proposed. The energy distribution in a 3-D DCT block, due to the nonstationary nature of the image data, varies along the veritical, horizontal and temporal directions. Thus, aiming an adaptive system to local variations, adaptive procedures, such as the 3-D classification, the classified linear scanning technique and the VLC table selection scheme, have been implemented in our approach. Also, a hybrid structure which adaptively combines inter-frame coding is presented, and it is found that the adaptive hybrid frame coding technique shows a significant performance gain for a moving sequence which contains a relatively small moving area. Through an intensive computer simulation, it is demonstrated that, the performance of the proposed 3-D transform coding technique shows a close relation with the temporal variation of the sequence to be code. And the proposed technique has the advantages of skipping the computationally complex motion compensation procedure and improving the performance over the 2-D motion compensated transform coding technique for rates in the range of 0.5 ~ 1.0 bpp.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.94-101
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• 2000

In this paper, a multi-channel active noise control(ANC) system using subband hybrid control techniques is proposed. Subband techniques could reduce computational burden and improve the performance of ANC systems by dividing several frequency subband and adjusting adaptive filter coefficients. So it can effectively cancel noises at wanted frequency range and use lower order adaptive filter than the existing algorithms. The adjoint LMS algorithm, which prefilter the error signals instead of the divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of the subband adaptive systems. To improve performance of the ANC system, a weighted hybrid control technique, which has weightily properties of feedforward control systems and feedback control systems, is applied. This algorithm shows higher stability and good noise attenuation property in broad band ANC systems. Computer simulations were performed to show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.370-374
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• 1999

The proposed algorithm used the Hybrid teaming rule in the input and hidden layer, and Back-Propagation teaming rule in the hidden and output layer. From the results of simulation of tracking control with one link manipulator as a plant, we verify the usefulness of the proposed control method to compare with common direct adaptive neural network control method; proposed hybrid teaming rule showed faster loaming time faster settling time than the direct adaptive neural network using Back-propagation algorithm. Usefulness of the proposed control method is that it is faster the learning time and settling time than common direct adaptive neural network control method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.139-147
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• 2003

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing such as signal prediction. This paper proposes the hybrid network, composed of locally(LRNN) and globally recurrent neural networks(GRNN), to improve dynamics of multilayered recurrent networks(RNN) and then describes nonlinear adaptive prediction using the proposed network as an adaptive filter. The hybrid network consists of IIR-MLP and Elman RNN as LRNN and GRNN, respectively. The proposed network is evaluated in nonlinear signal prediction and compared with Elman RNN and IIR-MLP networks for the relative comparison of prediction performance. Experimental results show that the hybrid network performs better with respect to convergence speed and accuracy, indicating that the proposed network can be a more effective prediction model than conventional multilayered recurrent networks in nonlinear prediction for nonstationary signals.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.176-178
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• 2004

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.775-785
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• 2008

We identify the problem of the current IEEE 802. lie HCCA (Hybrid Coordination Function Controlled Channel Access) scheduler and its numerous variations, that the queue information cannot be notified to the Hybrid Coordinator (HC) timely, therefore the uplink delay lengthens unnecessarily. We suggests a simple solution and a couple of implementation practices, namely the Adaptive Scheduler with RTS/CTS (ASR) and Adaptive Scheduler with Data/Ack (ASD). They are both further elaborated to emulate the Deficit Round Robin (DRB) scheduler. They are finally compared with existing exemplary schedulers through simulations, and shown to perform well.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.310-319
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• 2002

This paper deals with the analytical modeling, and the experimental verification of the strain rate self-sensing method using a hybrid adaptive filter for a cantilevered piezoelectric beam. The piezoelectric beam consists of two laminated lead zirconium titanates (PZT) on a metal shim. A mathematical model of the beam dynamics is derived by Hamilton's principle and the accuracy of the modeling is verified through the comparison with experimental results. For the strain rate estimation of the cantilevered piezoelectric beam, a self-sensing mechanism using a hybrid adaptive filter is considered. The discrete parts of this mechanism are realized by the DS1103 DSP board manufactured by dSPACE$\^$TM/. The efficacy of this method is investigated through the comparison of experimental results with the predictions from the derived analytical model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.265-270
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• 2006

Recently, inertial sensors like gyros and accelerometers have been quite miniaturized by Micro Electro-Mechanical Systems (MEMS) technology. JAXA is developing a MEM-based GPS/INS hybrid navigation system named Micro-GAIA. The navigation performance of Micro-GAIA was evaluated through off-line analysis by using flight test data. The estimation errors of the roll, pitch, and azimuth were $0.03^{\circ}$, $0.05^{\circ}$, $0.05^{\circ}$ $(1{\sigma})$, respectively. he horizontal position errors after 60-second GPS outages were reduced to 25 m CEP. The attitude errors and position errors are nearly half of ones reported previously[2]. Furthermore, using the adaptive Kalman filters, the robustness against the uncertainty of the measurement noise was improved. Comparing the innovation-based and residual-based adaptive Kalman filters, it was confirmed that the latter is robuster than the former.

• Smart Structures and Systems
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• v.24 no.1
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• pp.37-52
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• 2019

Despite its success and wide application, base isolation system has been challenged for its passive nature, i.e., incapable of working with versatile external loadings. This is particularly exaggerated during near-source earthquakes and earthquakes with dominate low-frequency components. To address this issue, many efforts have been explored, including active base isolation system and hybrid base isolation system (with added controllable damping). Active base isolation system requires extra energy input which is not economical and the power supply may not be available during earthquakes. Although with tunable energy dissipation ability, hybrid base isolation systems are not able to alter its fundamental natural frequency to cope with varying external loadings. This paper reports an overview of new adventure with aim to develop adaptive base isolation system with controllable stiffness (thus adaptive natural frequency). With assistance of the feedback control system and the use of smart material technology, the proposed smart base isolation system is able to realize real-time decoupling of external loading and hence provides effective seismic protection against different types of earthquakes.