• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1222-1227
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• 1990

The problem of identification of continuous systems is considered when both the discrete input and output measurements are contaminated by white noises. Using a predesigned digital low-pass filter, a discrete-time estimation model is constructed easily without direct approximations of system signal derivatives from sampled data. If the pass-band of the filter is designed so that it includes the main frequencies of both the system input and output signals in some range, the noise effects are sufficiently reduced, accurate estimates can be obtained by least squares(LS) algorithm in the presence of low measurement noises. Two classes of filters(infinite impulse response(IIR) filter and finite impulse response(FIR) filter) are employed. The former requires less computational burden and memory than the latter while the latter is suitable for the bias compensated least squares(BCLS) method, which compensates the bias of the LS estimate by the estimates of the input-output noise variances and thus yields unbiased estimates in the presence of high noises.

• ETRI Journal
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• v.31 no.2
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• pp.162-172
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• 2009

A linear-prediction-based blind equalization algorithm for single-input single-output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second-order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single-input multiple-output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum-mean-square-error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.68-74
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• 2004

The use of digital filters in the signal processing field is increasing rapidly with development of the modem industrial society, and generally digital filter is classified into FIR (infinite impulse response) fillers and FIR (finite impulse response) filters. The FIR digital filter has the phase linearity and the easiness of creation. In the design of the FIR digital filter, the window function is used to alleviate ripples caused by Gibbs Phenomenon around the cut-off frequency of the passband. In this paper, we designed a new window function and compared with existing Manning, Hamming and Blackman window functions. And we used peak side-lobe and transient characteristics as standard of judgement.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.109-117
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• 2002

Electrogastrography(EGG) is a noninvasive method for measuring gastric electrical activity on the abdomen resulting from gastric muscle. EGG signals have a very low frequency range (0.0083 ~0.15 Hz) and extremely low amplitude(10~100 uV). Consequently, EGG signal is easily influenced by other noises. Both finite impulse response(FIR) and infinite impulse response (IIR) filters need high orders or have phase distortions for passing very narrow bandwidth of the EGG signal. In this study, we decomposed EGG signals using a wavelet multiresolution method with Daubechies mother wavelet. The EGG signals were decomposed to seven levels. We reconstructed signal by summing the decomposed signals from level four to seven. To evaluate the performance of the wavelet multiresolution filter(WMF) with simulated EGG signal using two kinds of FIR and four kinds of IIR filters., we used two indices; signal to noise ratio(SNR) and reconstruction squared error(RSE). The SNR of WMF had 9.5, 6.9, and 4.7 dB bigger than that of the other filters at different noise levels, respectively. Also, The RSE of WMF had $1.22{\times}10^6, 1.16{\times}10^6, 1.02{\times}10^6$ smaller than that of the other filters at different noise levels, respectively. The WMF performed better in the SNR and RSE than two kinds of FIR and four kinds of IIR filters.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.58-60
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• 1987

In this paper, we investigate an infinite impulse response adaptive digital filter based on the nonlinear least-squares algorithm, and compare its convergence speed to that of a self-orthogonalizing IIR ADF which is known to have fastest convergence. By simulation, it is shown that the NLS IIR ADF converges faster than other known IIR ADF's, especially for a low-order case.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.189-193
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• 2003

A new algorithm is presented for adaptive notch filtering of narrow band or sine signals for embedded among broad band noise. The notch filter is implemented as a constrained infinite impulse response filter with a minimal number of parameters, Based on the recursive prediction error (RPE) method, the algorithm has the advantages of the fast convergence, accurate results and initial estimate of filter coefficient and its covariance is revealed. A convergence criterion is also developed. By using the information of the noise-to-signal power, the algorithm can self-adjust its initial filter coefficient estimate and its covariance to ensure convergence.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.389-390
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• 2023

본 논문에서는 헤어가 젖었을 때 표현되는 다양한 물리적 효과를 사실적으로 표현할 수 있는 알고리즘에 대해 제안한다. 젖은 헤어에서 나타는 곱슬 형태를 헬릭스 기반으로 모델링하여 젖었을 때 더욱더 과하게 표현되도록 하였으며, 큰 계산양 없이 효율적으로 젖은 곱슬 헤어를 효율적으로 표현하였다.

• The Journal of the Acoustical Society of Korea
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• v.6 no.3
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• pp.52-59
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• 1987

In this paper, we present a method of realizing an infinite impulse response (IIR) digital filter (DF)using linear delta modulation (LDM) as a simple analog/digital (A/D) converter. This method makes the realization of IIR digital filters much simpler than that of conventional ones because it does not require hardware multipliers and a pulse code modulation (PCM) A/D converter. Compared to the finite impulse respponse (FIR) LDMDF of Lee and Un [1] , this IIR LDMDF requires significantly less computation time.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.E2
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• pp.66-73
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• 2007

The introduction of tracer gas techniques to ventilation studies in indoor environments provides valuable information that used to be unattainable from conventional testing environments. Data acquisition systems (DASs) containing analogue-to-digital (A/D) converters are usually used to function the key role that records signals to storage in digital format. In the testing process, there exist a number of components in the measuring equipment which may produce system-based inference to the monitored results. These unwanted fluctuations may cause significant error in data analysis, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and applied to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are monitored during leakage and ventilation tests in the model test room. The signal analysis functions are introduced to carry out the digital signal processing (DSP) work. Overall the FIR filters process the $CO_2$ measurement properly for ventilation rate and mean age of air calculations. It is found that, the Kaiser filter was the most applicable digital filter for pre-processing the tracer gas measurements. Although the IIR filters help to reduce the random noise in the data, they cause considerable changes to the filtered data, which is not desirable.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.159-162
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• 2005

Recently, due to rapid developments of wireless communication and digital TV, modern society needs to process of aquisition, storage and transmission of much information. So the importance of signal processing is increasing and various digital filters are used in the two-dimensional signal such as image. And kinds of these digital filters are IIR(infinite impulse response) filter and FIR(finite impulse response) filter. And FIR filter which has the phase linearity, the easiness of creation and stability is applied to many fields. In design of this FIR filter, flatness property is a important factor in pass-band and stop-band. In this paper, we designed a 2-D Circular FIR filter using the Bernstein polynomial, it is presented flatness property in pass-band and stop-band. And we simulated the designed filter with noisy test image and compared the results with existing methods.