• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.7-12
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• 1993

This paper presents a generalized truncated least, squares adaptive algorithm and a two-stage design method. The proposed algorithm is directly derived from the normal equation of the generalized truncated least squares method (GTLSM). The special case of the GTLSM, the truncated least squares (TLS) adaptive algorithm, has a distinct features which includes the case of minimum steps estimator. This algorithm seemed to be best in the deterministic case. For real applications in the presence of disturbances, the GTLS adaptive algorithm is more effective. The two-stage design method proposed here combines the adaptive control system design with a conventional control design method and each can be treated independently. Using this method, the validity of the presented algorithms are examined by the simulation studies of an indirect adaptive control.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.46-50
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• 2001

Adaptive signal processing is used to acoustic echo canceller. adaptive noise canceller and adaptive algorithm among adaptive algorithms is mainly used because the structure is simple and computa LMS algorithm has trade-off between the converge speed and the steady state error. In this paper, step-size of adaptive algorithm is varied with orthogonality Principles of optimal filter to get fasts though small steady state error. Time varying step-size is determined proportional to the maximum vector of LMS algorithm. As results of simulations, the adaptive algorithm with proposed time-v compared with conventional ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.673-682
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• 2004

The adaptive beam-forming is promising approach for noise reduction in hearing aids. This approach has come in the focus of interest only recently, because of the availability of new and powerful digital signal processors. The adaptation U using usually a Least Mean Squares algorithm, updates the weight vector. In this Paper, we propose a fast wavelet based adaptive algorithm using variable step size algorithm which varies adaptive constant by the change of signal environment. We compared the performance of the proposed algorithm with the known adaptive algorithm using computer simulation of multi channel adaptive bemformer in hearing aids. As the result the proposed algorithm is suitable for adaptive signal processing area using hearing aids and has advantages reducing computational complexity. And we show the beam-forming system using proposed algorithm converges stably in a sudden change of system environment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.4
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• pp.1-9
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• 2007

in this paper, we propose the Adaptive Decision Algorithm for RFID Tag Anti-Collision. We study the RFID Tag anti-collision technique of ALOHA and the anti-collision algorithm of binary search. The existing technique is several problems; the transmitted data rate included of data, the recognition time and energy efficiency. For distinction of all tags, the Adaptive Decision algorithm identify smaller one ,each Tag_ID bit's sum of bit '1'. In other words, Adaptive Decision algorithm had standard of selection by actively, the algorithm can reduce unnecessary number of search even than the exisiting algorithm. The Adaptive Decision algorithm had performance test that criterions were reader's number of repetition and number of transmitted bits for understanding tag. We showed the good performance of Adaptive Decision algorithm better than exisiting algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.19-25
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• 2012

An adaptive system is a well-known method for removing noise from noise-corrupted speech. In this paper, we perform a least mean square (LMS) based on wavelet adaptive algorithm. It establishes the faster convergence rate of as compared to time domain because of eigenvalue distribution width. And this paper provides the basic tool required for the FIR algorithm whose algorithm reduces the arithmetic complexity. We consider a new fast short-length running FIR structure in discrete wavelet adaptive algorithm. We compare FIR algorithm and short-length fast running FIR algorithm (SFIR) to the proposed fast short-length running FIR algorithm(FSFIR) for arithmetic complexities.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.4
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• pp.17-21
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• 2002

Least mean square(LMS) algorithm one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency. in this paper, ie use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a high speed wavelet based adaptive algorithm with variable step size, which is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.89-96
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• 2016

The performance of anti-submarine sonar detection is required to improve by the development of submarine noise reduction technology. because of the need of an anti-submarine detection ability, known for superior beamforming performance, adaptive beamforming algorithms have been considered as an alternative beamforming algorithm of a conventional beamforming algorithm. In order to achieve improved performance by applying an adaptive beamforming algorithm to the sonar system, the adaptive beamforming algorithm applicability of system must be verified, To do this, the performance index for the system applicability must be established. In this paper, a tracking initiation probability of the adaptive beamforming algorithm and the conventional beamforming algorithm was calculated and the performance of both techniques was quantified, a system applicability of the adaptive beamforming algorithm was reviewed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1183-1186
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• 1998

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.