• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1312-1320
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• 2009

This paper presents an efficient design method of 2-D infinite impulse response(IIR) digital filter based on a particle swarm optimization(PSO) algorithm. The design task is reformulated as a constrained minimization problem and is solved by our newly developed PSO algorithm. To ensure the stability of the designed 2-D IIR digital filters, a new stability strategy is embedded in the basic PSO algorithm. The superiority of the proposed method is demonstrated by several experiments. The results show that the approximation error of the resultant filters are better than those of the digital filters which designed by recently published filter design methods. The proposed design method can also obtain the stable2-D IIR digital filters.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.413-418
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• 2003

In this paper, a new multirate optimal finite impulse response (FIR) filter is proposed for the signal reconstruction in the nosy filter bank systems. The multirate optimal FIR filter replaces the conventional synthesis filters and the Kalman synthesis filter. First, the generic linear model is derived from the multirate state space model for an autoregressive (AR)input signal. Second, the multirate optimal FIR filter is derived from the multirate generic linear model using the minimum variance criterion. This paper also provides numerical examples and results. The simulation results illustrate that the performance is improved compared with conventional synthesis filters and the proposed filter has advantages over the Kalman synthesis filter.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.351-354
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• 2007

In recent years, digital processing techniques have been applied diversity of fields. Typical signal processing techniques are speech processing and image processing. And filters for the signal processing can be divided in FIR (finite impulse response) filter and IIR (infinite impulse response) filter. Compared with IIR filter, the FIR Filter has a defect of high-degree, but has a merit of stability and uses simply. Futhermore, FIR filter also has linear phase response characteristics, it is using in fields regarding wave information importantly. To FIR Filter design, the main issue is to remove the Gibbs phenomenon. Therefore, in this paper I was proposed a method using FIR digital filter applied a modified window function and the method was compared with conventional methods.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.145-155
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• 1990

In this paper, an adaptive Infinite Impulse Response (IIR) filter algorithm using output error method, which prevents poles of a system transfer function from being out of unit circle, is proposed, and it is proved that the proposed algorithm always satisfies hyperstability. The proposed algorithm is applied to an Adaptive Noise Canceller (ANC), and compared with a Least Square (LS) method adaptive IIR filter algorithm and an adaptive Finite Inpulse Response (FIR) filter algorithm. As a result, the validity of the proposed algorithm is proved.

• 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 Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.310-312
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• 2011

In complex noise environment, digital filter is being used to obtain, transport and storage original voice or image signal. Digital filter can be largely separated FIR(Finite duration impulse response) filter and IIR(Infinite duration impulse response) filter. Among FIR filter, window function has characteristic of linear phase and as can be easily set pass-band frequency, cutoff frequency and so on. In this paper, We compared with established method using transient characteristic and peak side-lobe in order to check filter characteristics after we designed the existing variants of the window function.

• 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 Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.10
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• pp.1518-1523
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• 2012

In this study, the novel digital filtering algorithms are implemented to suppress the noisy characteristics embedded in ambulatory electrocardiogram signals by an android smartphone platform. With this aim, Graphical User Interface (GUI) is designed and implemented by utilizing multithread-Java programming to realize Finite Impulse Response and Infinite Impulse Response filter. With simulating our implemented digital filters built in an android smartphone, we can find the fact that we can efficiently suppresses the noisy characteristics due to baseline wandering and 60 Hz powerline source fluctuations especially in electrocardiograms.

• 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.