• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.53-64
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• 1996

The methods for designing the adaptive filter performing DSP(digital signal processing)functions In mobile communication systems are Least-squares algorithm. Fast-Kalman and adaptive lattice algorithm. Least-squares algorithm It fast convergence algorithm for signal Processor of adaptive equallizer and used for eliminating inter symbol Interference which occur inmultiple path fading channel In mobille communication systems. In this paper. we propose the method of control adjustably algebra characteristics of signal vector that is sampling at some of new data sequence and confirm the improvement of fast convergence and iterative performance speed compared to existing algorithms by computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1767-1775
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• 2003

The SAW device is extensively used as a electro$.$mechanical band­pass filter in which a two­pairs of interdigital transducers are provided over the surface of the piezoelectric substrate. For the design requirement, the central frequency and the bandwidth of the passband, and the attenuation level of the stopband region are specified. The configuration is made so as to satisfy the specification given. The central frequency is mainly determined by the distance between the pair of the finger electrodes. The design is considered as an optimization problem with which the error norm, the distance between the desired characteristics and the calculated for a given model is to be minimized. The delta function model and the electrical equivalent circuit model are utilized to represent the SAW filter characteristics. Genetic algorithm is used for optimization in which apodization of the transducer fingers is chosen as a design variable.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2523-2532
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• 1994

In this paper, active noise control is performed in a duct system using the periodic pulse train which corresponds to the periodic component of noise source as a reference signal. Control algorithm applied in this study is possible to eliminate the acoustic feedback which occurs in the conventional filtered-x and filtered-u LMS algorithm by using electrical reference signal and has the fast adaptation speed with low filter orders by using synchronous sampling method is discussed via computer simulations and experiments of case studies such as frequency modulation, amplitude modulation and frequency differency between source signal and reference signal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1518-1531
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• 1999

The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2474-2479
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• 2011

As society has developed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized. However, image data is always corrupted by various noises during image processing, so researches for removing noises have been continued until now. In this paper, in order to remove impulse noise we proposed modified adaptive switching median filter that consists of two stages: noise detection and noise removal. Proposed algorithm only processes noise pixels and these noise pixels are replaced by filter output, so proposed algorithm performs well not only removes noise but also preserves edge information. Also we compare existing methods using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect and choose conventional algorithms to compare with our proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.15-22
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• 2012

This paper deals with the performance comparison and evaluation of blind adaptive equalizer, the PMCMA-MDD and DW-MCMA, that is used for compensation of the amplitude and phase distortion which occurs in the time dispersive channel. Basically, these algorithms are modification of MCMA cost function in order to obtain the fast convergence speed and reduced residual isi by taking the parallel and serial double structured and the combination of the concept of RCA for the updating the tap coefficient. We implements the algorithm of it and compare the recovered constellation, residual isi, MSE characteristics curve and SER in the signal to noise ratio given the time dispersive channel. As a result of simulation, the PMCMA-MDD has a good in recovered constellation than DW-MCMA. But in the SER, the DW-MCMA has a good than PMCMA-MDD.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.478-486
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• 2007

Double-talk detection errors can result in either large residual echo or distorting the near-end talker's input speech. Thus accurate double-talk detection is an important problem in the acoustic echo canceller to improve the speech quality. In the double-talk detection algorithm using a cross-correlation coefficient, double-talk detection errors can occur in the initial convergence period of an adaptive filter or in noisy environment since the cross-correlation coefficient becomes large in such situations. In this paper, we propose a new double-talk detection algorithm based on the cross-correlation method using a normalized error signal power to reduce the double-talk detection errors. The experimental results have shown the performance improvement of an acoustic echo canceller as well as the noise-robustness of the proposed double-talk detector.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1103-1108
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• 2023

In this paper, we propose a new algorithm for attenuating the background noises in acoustic signal. This algorithm improves the noise attenuation performance by using the FNN(: Full-connected Neural Network) deep learning algorithm instead of the existing adaptive filter after wavelet transform. After wavelet transforming the input signal for each short-time period, noise is removed from a single input audio signal containing noise by using a 1024-1024-512-neuron FNN deep learning model. This transforms the time-domain voice signal into the time-frequency domain so that the noise characteristics are well expressed, and effectively predicts voice in a noisy environment through supervised learning using the conversion parameter of the pure voice signal for the conversion parameter. In order to verify the performance of the noise reduction system proposed in this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed. As a result of the experiment, the proposed deep learning algorithm improved Mean Square Error (MSE) by 30% compared to the case of using the existing adaptive filter and by 20% compared to the case of using the STFT(: Short-Time Fourier Transform) transform effect was obtained.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.4
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• pp.38-48
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• 1982

Performance and realization of finite impulse response (FIR) digital filters that use an adaptive delta modulator (ADM) as an analog/digital converter have been studied. This filter requires no multiplication and offers many advantages over conventional PCM filters in low power consumption, small size, and cost effectiveness. Analytical formulas have been derived for the expected mean-squared errors and also for the word length necessary to achieve the desired performance. Computer simultation has been done to optimize the parameter values and to verify the results of performance analysis. In addition, design of FIR ADM digital filters for processing single and multi-channel signals has been considered.