• The Journal of the Acoustical Society of Korea
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• v.16 no.2E
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• pp.14-20
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• 1997

The future teleconferencing systems will need an appropriate system which controls properly the acoustic echo for the convenient communication. The conventional acoustic echo cancellation algorithms involve large adaptive filters identifying the impulse response of the echo path. The use of adaptive IIR filters appears to be a reasonable way to reduce computational complexity. Effective cancellation of acoustic echo presented in teleconferencing system requires that adaptive filters have a rapid convergence speed. One of the main problems of acoustic echo cancellation techniques is that the convergence properties degrade for an highly correlated signal input such as speech signals. By the way, the introduction of linear prediction filers onto the structure of the acoustic echo cancellation represents one approach to decorrelate the speech signal. And variable step-size LMS algorithm improves the convergence speed through a little increasing of computational complexity. In this paper, we applied these two methods to the acoustic echo canceller(AEC) and showed that these methods have better performances than the conventional AEC.

• Journal of the military operations research society of Korea
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• v.13 no.1
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• pp.1-18
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• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.285-294
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• 2004

Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.681-684
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• 2000

Gradient-type algorithms for adaptive IIR notch filters are very attractive in terms of both performances and computational requirements. Generally, it is quite difficult to assess their performances analytically. There have been several trials to analyze such adaptive algorithms as the sign and the plain gradient algorithms for some types of adaptive IIR notch filters, but many of them still remain unexplored. Furthermore, analysis techniques used in those trials can not be directly applied to different types of adaptive IIR notch filters. This paper presents a detailed performance analysis of the sign algorithm for a well-known adaptive IIR notch filter with constrained poles and zeros, which can not be done by just applying the related existing analysis techniques, and therefore has not been attempted yet. The steady-state estimation error and mean square error (MSE) of the algorithm are derived in closed forms. Stability bounds of the algorithm are also assessed. extensive simulations are conducted to support the analytical findings.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.285-291
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• 2001

In this paper, we designed two preprocessing adaptive filter - high pass filter and notch filter - using FPGA. For minimizing the calculation load of multi-channel and high-resolution ECG system, we utilize FPGA rather than digital signal processing chip. To implement the designed filters in FPGA, we utilize FPGA design tool(Altera corporation, MAX-PLUS II) and CSE database as test data. In order to evaluate the performance in terms of processing time, we compared the designed filters with the digital filters implemented by ADSP21061(Analog Devices). As a result, the filters implemented by FPGA showed better performance than the filters based on ADSP21061. As a consequence of examination, we conclude that FPGA is a useful solution in multi-channel and high-resolution signal processing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.876-883
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• 1996

Adaptive FIR filters are widely used in the echo canceller. But, most of practical systems have the transfer function composed of poles and zeros. In that case, adaptive IIR filters may be more efficient rather than FIR fiters. In this paper, a recently developed C-HARF algorithm is used to implement an adaptive IIR echo canceller. The proposed convergence of the algorithm make it attractive for this application. Extensive computer simulations show that C-HARF algorithm performs better than the NLMS algorithm after convergence, although C-HARF algorithm converges more slowly.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.34-42
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• 1992

This paper presents two fast least-squares lattice algorithms for adaptive nonlinear filters equipped with bilinear system models. The lattice filters perform a Gram-Schmidt orthogonalization of the input data and have very good numerical properties. Furthermore, the computational complexity of the algorithms is an order of magnitude snaller than previously algorithm is an order of magnitude smaller than previously available methods. The first of the two approaches is an equation error algorithm that uses the measured desired response signal directly to comprte the adaptive filter outputs. This method is conceptually very simple`however, it will result in biased system models in the presence of measurement noise. The second approach is an approximate least-squares output error solution. In this case, the past samples of the output of the adaptive system itself are used to produce the filter output at the current time. Results of several experiments that demonstrate and compare the properties of the adaptive bilinear filters are also presented in this paper. These results indicate that the output error algorithm is less sensitive to output measurement noise than the squation error method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.133-139
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• 2013

Convex combination of two adaptive filters is an efficient method to improve adaptive filter performances. In this paper, a subband convex combination method of two adaptive filters for fast convergence rate in the transient state and low steady state error is presented. The cost function of mixing parameter for a subband convex combination is defined, and from this, the coefficient update equation is derived. Steady state analysis is used to prove the stability of the subband convex combination. Some simulation examples in system identification scenario show the validity of the subband convex combination schemes.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.295-303
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• 2008

In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).