• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.443-446
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• 2005

As modern society needs to process of acquisition, storage and transmission of much information, 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.

• Journal of IKEEE
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• v.3 no.1 s.4
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• pp.11-21
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• 1999

This paper has been proposed a structure composed of FIRs and IIR filters as digital interpolation filter to integrate the off-chip analog low-pass filter of audio DAC. The passband ripple (>$0.41{\times}fs$), passband attenuation(>at$0.41{\times}fs$) and stopband attenuation(<$0.59{\times}fs$) of the ${\Delta}{\Sigma}$ modulator output using the proposed digital interpolation filter had ${\pm}0.001[dB]$, -0.0025[dB] and -75[dB], respectively. Also the inband group delay was 30.07/fs[s] and the error of group delay was 0.1672%. Also, the attenuation of stopband has been increased -20[dB] approximately at 65[kHz], out-of-band. Therefore the RC products of analog low-pass filter on chip have been decreased compared with the conventional digital interpolation filter structure.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.563-568
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• 2023

ECG(electrocardiogram) is used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, Noise included in the ECG signal was removed by using a lowpass filter of the Digital FIR Hamming window function. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, which was confirmed that the activation function with the smallest error was the tanh() function, the elapsed time was longer when the batch size was small than large. Also, it was confirmed that result of the performance evaluation for the GRU model was superior to that of the LSTM model.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.13-20
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• 2001

Adaptive digital filters with long impulse response such as acoustic echo canceller and active noise controller suffer from slow convergence and computational burden. Subband techniques and multirate signal processing have been recently developed to improve the problem of computational complexity and slow convergence in conventional adaptive filter. Any FIR transfer function can be realized as a serial connection of interpolators followed by subfilters with a sparse impulse response. In this case, each interpolator which is related to the column vector of Hadamard matrix has band-pass magnitude response characteristics shifted uniformly. Subband technique using Hadamard transform and decimation of subband signal to reduce sampling rate are adapted to system modeling and acoustic noise cancellation In this paper, delayless subband structure with nonuniform bandwidth has been proposed to improve the performance of the convergence speed without aliasing due to decimation, where input signal is split into subband one using tree-structured filter bank, and the subband signal is decimated by a decimator to reduce the sampling rate in each channel, then subfilter with sparse impulse response is transformed to full band adaptive filter coefficient using Hadamard transform. It is shown by computer simulations that the proposed method can be adapted to general adaptive filtering.