• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.58-63
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• 2007

GPS signal is vulnerable to intentional and unintentional interferences since it has a very weak signal power and its structure is well-known. Among the interference rejecting techniques, the ATF is being generally used as a pre-correlation technique. However, it does not have a design parameter relating to the notch width, resulting in the spectral loss around frequency of the interference. The IIR notch filter has a design parameter relating to the notch width and can generate a sharp notch for the CW interference. In this paper, an adaptive IIR notch filter is proposed and the performance is evaluated using software signal generator and real measurements.

• Elastomers and Composites
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• v.23 no.4
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• pp.308-323
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• 1988

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6A
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• pp.341-350
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• 2003

In this paper, we evaluate the performance of a moving average (MA) channel estimation filter when space-time block coding transmit diversity (STBC-TD) is applied to the wideband direct sequence code division multiple access (WCDMA) forward link. And we present the infinite impulse response (IIR) filter scheme that can reduce the required memory buffer and the channel estimation delay time. This paper also compares the performance between MA filter scheme and IIR filter scheme in various Rayleigh fading channel environments through the bit error rate (BER) and the frame error rate (FER). Extensive computer simulation results show that transmission with STBC-TD provides a significant gain in performance over no transmit diversity technique, particularly at pedestrian speeds. If STBC-TD technique is employed in the channel estimator based on MA filter, it provides considerable performance gains against Rayleigh fading and reduces the optimum filter tap number. Consequently, the channel estimation delay time and the complexity of the receiver are reduced. In addition, the channel estimator based on IIR filter has the advantages such as little memory requirement and no delay time compared to the MA scheme. However, IIR filter coefficients is very sensitive to the mobile speed change and it exerts a serious influence upon the performance. For that reason, it is important to set uP the optimum IIR filter coefficients.

• Journal of Environmental Science International
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• v.17 no.1
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• pp.107-112
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• 2008

A study on the enhancement of environmental durability of EPDM rubber materials for the aerator membrane was performed using a butyl rubber as a modifier. A conventional EPDM rubber formulation was evaluated as having about 26.0 wt% or more oil content from the chloroform immersion test. These oils would be gradually and continuously deleted from the aerator membrane when directly exposed to a waste-water or chemically corrosive fluids, making the membrane less flexible and the performance worse. To improve this, a butyl rubber (IIR) was utilized as the modifier for a low-ENB type of EPDM rubber formulation with low-oil content. The environmental durability of the IIR-modified EPDM rubber material was expected to be greatly enhanced compared to the conventional one. However, the mechanical and performance properties such as elongation, tensile strength, and air bubble size, etc. were still maintained as good as in the conventional one. Furthermore, TGA analysis of the IIR-modified EPDM material showed that there would be partially compatible between IIR and EPDM. It also showed that the initial degradation temperature of the IIR-modified EPDM could be somewhat increased, exhibiting the enhanced compatibility among the components and, thereby, more enhanced environmental durability.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.8
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• pp.375-377
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• 2006

An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• 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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• 2006.04a
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• pp.30-32
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• 2006

An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be Improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1700-1705
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• 2012

This study is focusing on ripple elimination in the band pass filter. There are generally two design methods in IIR filter design, which are a direct method and an indirect one. The indirect design method that designs the digital IIR LPF using the prototype analog LPF is applied to this study. A Butterworth filter and a Chebyshev filter are the typical prototype analog LPFs. This study shows characteristics of the digital IIR LPFs that are transformed from the prototype analog LPFs. The designed Butterworth and Chebyshev IIR LPFs are also designed as the band pass filters by frequency transformation in order to compare with the proposed cascading Chebyshev BPFs. This study shows frequency characteristics between the transformed IIR BPFs and the proposed cascading Chebyshev BPFs as well. The proposed cascading Chebyshev BPF is designed by cascading the different orders of Chebyshev BPFs. The aspect of the cascading filter is offsetting the ripples to descend them while the pass band ripples of the Chebyshev filter are ascending and vice versa. The designed cascading Chebyshev filter shows the flatness and the sharpness, which represent the advantages of Butterworth filter in the pass band and of Chebyshev filter in the transition band respectively. This result verifies the validity of the designed filter.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1230-1242
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• 2007

This paper describes an IIR/FIR fusion filter for a nonlinear system, and analyzes the stability of the fusion filter. The fusion filter is applied to INS/GPS integrated system, and the performance is verified by simulation and experiment. In the fusion filter, an IIR-type filter (SPKF) and FIR-type filter (MRHKF filter) are processed independently, then the two filters are merged using the mixing probability calculated using the residuals and residual covariance information of the two filters. The merits of the SPKF and the MRHKF filter are embossed and the demerits of the filters are diminished via the filter fusion. Consequently, the proposed fusion filter has robustness against to model uncertainty, temporary disturbing noise, large initial estimation error, etc. The stability of the fusion filter is verified by showing the closeness of the states of the two sub filters in the mixing/redistribution process and the upper bound of the error covariance matrices. This fusion filter is applied into INS/GPS integrated system, and important factors for filter processing are presented. The performance of the INS/GPS integrated system designed using the fusion filter is verified by simulation under various error environments and is confirmed by experiment.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.45-52
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• 2005

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing. This paper describes system identification using the hybrid neural network, composed of locally(LRNN) and globally recurrent neural networks(GRNN) to improve dynamics of multilayered recurrent networks(RNN). The structure of the hybrid nework combines IIR-MLP as LRNN and Elman RNN as GRNN. The hybrid network is evaluated in linear and nonlinear system identification, and compared with Elman RNN and IIR-MLP networks for the relative comparison of its performance. Simulation results show that the hybrid network performs better with respect to the convergence and accuracy, indicating that it can be a more effective network than conventional multilayered recurrent networks in system identification.