• The Journal of the Acoustical Society of Korea
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• v.33 no.5
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• pp.309-315
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• 2014

In this paper, a novel variable step-size filtered-x gradient adaptive lattice (NVSS-FxGAL) algorithm for active noise control system is proposed. The gradient adaptive lattice (GAL) algorithm is capable of controlling the narrow band noise effectively. The GAL algorithm can achieve both fast convergence rate and low steady-state level using the variable step-size. However, it suffers from the convergence performance for varying signal characteristic since the global variable step-size is equally applied to all lattice stages. Therefore, the proposed algorithm guarantees the stable and consistency convergence performance by using the local variable step-size for the suitable each lattice stage. Simulation results confirm that the proposed algorithm can obtain the fast convergence rate and low steady-state level compared to the conventional algorithms.

• Korean Journal of Optics and Photonics
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• v.13 no.3
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• pp.251-257
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• 2002

The measuring resolution and speed for wavefronts are important to improve the performance of an adaptive optics system. In this paper, we propose a fast measuring algorithm with high resolution in the Shack-Hartmann wavefront sensor for an adaptive optics system. We designed ground isolated electrical devices whose differential data signals are used to control the deformable mirror and tip/tilt mirror for robust control. The conventional mass centroid algorithm in the Shack-Hartmann sensor to measure wavefront has been widely used and provided good measurement results. In this paper, the proposed fast measuring algorithm for measuring the wavefront combines the conventional mass centroid algorithm with a weighting factor. The weighting factor is a real value estimating the real center of mass in a wavefront spot image. This proposed wavefront measuring algorithm provided fast measurement results with high resolution from experimental tests.

• Journal of IKEEE
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• v.13 no.1
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• pp.1-10
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• 2009

Recently, some frequency domain CMA (Constant Modulus Algorithm) have been introduced in an effort to reduce computational complexities [1,2]. In [1], a fast algorithm that minimizing cost function designed for block input signal is employed, while in [2], a novel cost function that minimizing sample by sample input is used. Although, the two fast algorithm save computational complexities as compared to CMA, the convergence behaviors of the two fast algorithm show different results with repsect to CMA. Thus, in this paper, some analytical results on the error surface of the fast frequency domain CMA are introduced. From the analytical results, we show that the more recent algorithm [2] outperforms the previous algorithm [1]. Simulation results reveals that the recent algorithm [2] shows 50% enhanced convergence with respect to the old fast algorithm [1]. Also, we show that the recent fast algorithm [2] has comparable convergence performance with respect to conventional CMA algorithm.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.721-725
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• 2014

In this paper, we propose a fast adaptive power allocation method for an orthogonal frequency division multiple access (OFDMA) system that employs an adaptive modulation and coding (AMC) scheme. The proposed scheme aims to reduce the calculation complexity of greedy adaptive power allocation (APA), which is known as the optimal algorithm for maximizing the utility argument of power. Unlike greedy APA, which starts power allocation from "0", the proposed algorithm initially allocates a certain level of power determined by the water-filling scheme. We theoretically demonstrate that the proposed algorithm has almost the same capability of maximizing the utility argument as the greedy APA while reducing the number of operations by 2M, where M is the number of AMC levels.

• Proceedings of the Acoustical Society of Korea Conference
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• 1987.11a
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• pp.79-81
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• 1987

In this paper we propose a fast adaptive least squares algorithm for linear phase FIR filters. The algorithm requires 10m multiplications per data point where m is the filter order. Both linear phase cases with constant phase delay and constant group delay are examined. Simulation results demonstrate that the proeposed algorithm is superior to the LMS gradient algorithm and the averaging scheme used for the modified fast Kalman algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1107-1119
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• 2006

Data transmission experiences multiplicative distortion in frequency nonselective fading channel. This distortion occurs in OFDM communication channel and can be compensated using an equalizer. Usually, in the case of LMS equalizer, eigenvalue distribution of training signal is enlarged. Large eigenvalue distribution causes principally the performance of a communication system to be deteriorated. This paper proposes a new algorithm that shows the same performance as the existing fast wavelet transform algorithm with less computational complexity. The proposed algorithm was applied to an adaptive equalizer of OFDM communication system. Matlab simulation results show a better performance than the existing one. The proposed algorithm was implemented in VHDL and simulated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1249-1265
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• 1991

In this paper, a fast and adaptive feature extraction algorithm for textured image segmentation is proposed. First, a conventional algorithm to extract the statistical texture features are described and we obtain the recursive equations from that conventional method and it is used for extraction of sevaral texture features. And also we propose the adaptive algorithm which extract the texture features. To evaluate the performance of proposed algorithm, we apply the proposed method to artificial texture images. From the results of computer simulation, the proposed method is superior to the conventional one.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.17-26
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• 2011

We have developed a wearable device that can convert sensor data into real-time step counts. Sensor data on gait were acquired using a triaxial accelerometer. A test was performed according to a test protocol for different walking speeds, e.g., slow walking, walking, fast walking, slow running, running, and fast running. Each test was carried out for 36 min on a treadmill with the participant wearing an Actical device, and the device developed in this study. The signal vector magnitude (SVM) was used to process the X, Y, and Z values output by the triaxial accelerometer into one representative value. In addition, for accurate step-count detection, we used three algorithms: an heuristic algorithm (HA), the adaptive threshold algorithm (ATA), and the adaptive locking period algorithm (ALPA). The recognition rate of our algorithm was 97.34% better than that of the Actical device(91.74%) by 5.6%.

• 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.