• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.10C
• /
• pp.1007-1012
• /
• 2003

In order to accelerate the convergence speed of the conventional BP algorithm, constrained optimization techniques are applied to the BP algorithm. First, the noise-constrained least mean square algorithm and the zero noise-constrained LMS algorithm are applied (designated the NCBP and ZNCBP algorithms, respectively). These methods involve an important assumption: the filter or the receiver in the NCBP algorithm must know the noise variance. By means of extension and generalization of these algorithms, the authors derive an adaptive error-constrained BP algorithm, in which the error variance is estimated. This is achieved by modifying the error function of the conventional BP algorithm using Lagrangian multipliers. The convergence speeds of the proposed algorithms are 20 to 30 times faster than those of the conventional BP algorithm, and are faster than or almost the same as that achieved with a conventional linear adaptive filter using an LMS algorithm.

• The Journal of the Acoustical Society of Korea
• /
• v.37 no.1
• /
• pp.66-72
• /
• 2018

In this paper, we propose an adaptive beamforming algorithm of triplet arrays for active sonar systems. The proposed algorithm consists of three steps: matched filters, cardioid beamforming, and line array beamforming. First, we apply a matched filter of a transmitted pulse to received individual sensor signals and obtain filterd signals. Then, we perform the fast Fourier transform to the matched filter results, and make a cardioid beam for each triplet data, respectively. Finally, we apply an adaptive beamforming by assuming that the cardioid beams are input signals of a line array. Experimental results demonstrate that the proposed algorithm provides better performances than conventional algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.2 s.314
• /
• pp.19-26
• /
• 2007

In the sigma filter, there is a specialized neighbours distribution scheme in which the sigma value is computed from local statistics. It is designed to modify a standard average filter to preserve edges. However this filter is vulnerable to details-enhancement and conventional sigma approaches have been focused on denoising, not enhancing the characteristic area. This paper proposes an adaptive image enhancement algorithm using local statistics and functional synthesis which are utilized for adaptive realization of the enhancement, so that not only image noise may be smoothed but also details may be enhanced. For the local adaptation, parameters are estimated and weighted at each moving window that satisfy the criteria. The experimental results illuminates the effectiveness of the proposed method.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.4
• /
• pp.288-294
• /
• 2008

In this paper, we proposed an algorithm of edge enhancement to improve image visibility of mobile phone camera. For naturally edge enhancement, we grasps edge characteristic in image and applied to the most appropriate enhancement value adaptively about each characteristics. Namely, It applies 2D high pass filter where in the edge characteristics which judge in the first In compliance with the edge condition which is subdivided more with secondary it will be able to apply the process which able to adaptive edge enhancement to improve image visibility. It joins in and it is an existing algorithm that simply a lies 2D high pass filter where and it is identical in the image whole it will be able to improve the side effects of ringing actual condition etc. It considers the effectiveness of the hardware resource with the hardware of the algorithm which is developed and algorithm the maximum simply, it developed and simulation of the algorithm which is proposed it led and algorithm of existing and it compared and is improved the result which it confirmed.

• Journal of Power System Engineering
• /
• v.18 no.5
• /
• pp.129-136
• /
• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• Journal of KSNVE
• /
• v.2 no.2
• /
• pp.107-116
• /
• 1992

An adaptive signal processing technique is implemented for the active noise cancellation of the plane acoustic wave propagating in a duct. To avoid the instability caused by the acoustic feedback from the control speaker to the detect microphone, an off-line modeling of the acoustic feedback plant is done using the FIR filter. Auxiliary path required for the filtered-x LMS algorithm is modeled as well. Before going into the experiments, a simulation is carried out under the same conditions with experiments. The simulation shows that the longer the length of the adaptive filter is, the better the results are achieved. Experiments have been carried out at lower audio frequency range (50 - 400Hz), and the results are in good agreements with those of simulation study. As a results of this adaptive noise control, around 50dB is reduced for a pure tone noise, and for a bandlimited noise with the bandwidth of 316Hz, a maximum of 30dB noise reduction is attained.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.2
• /
• pp.423-430
• /
• 2011

In adaptive filtering, the sparseness of impulse response and input signal characteristics are very important factors of it's performance. This paper presents a subband improved proportionate normalized least square (SIPNLMS) algorithm which combines IPNLMS for impulse response sparseness and subband filtering for prewhitening the input signal. As drawing and combining the advantage of conventional approaches, the proposed algorithm, for impulse responses exhibiting high sparseness, achieve improved convergence speed and tracking ability. Simulation results, using colored signal(AR(4)) and speech input signals, show improved performance compared to fullband structure of existing methods.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.11
• /
• pp.2299-2301
• /
• 2009

The adaptive IIR filters for active noise control systems are more effective when acoustic feedback exists, but the adaptive IIR filters could be unstable when the filter algorithm is not yet converged. In this paper, auto-secondary path estimation techniques and a stabilizing process for adaptive Multi-Channel Recursive LMS (MCRLMS) filters are developed to improve the stability of multi-channel active noise control systems. Experiments using a TMS320VC33 digital signal processor in a three dimensional enclosure have performed to show the effectiveness of the proposed algorithm.

• Management & Information Systems Review
• /
• v.3
• /
• pp.201-214
• /
• 1999

Adaptive correlator receiver with neural network based on complex multilayer perceptron is persented for suppressing interference of narrow-band of direct spread spectrum communication systems. Recursive least square algorithm with backpropagation error is used for fast convergence and better performance in adaptive correlator scheme. According to signal noise and transmission power, computer simulation results show that bit error ratio of adaptive correlator using neural network improved that of adative transversal filter of direct sequence spread spectrum considering of jamming and narrow-band interference. Bit error ratio of adaptive correlator with neural network is reduced about 10-1 than that of adaptive transversal filter where interference versus signal ratio is 5dB.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.6A
• /
• pp.568-574
• /
• 2002

The main issue of noise reduction of image is how to preserve edge and reduce noise. Usually, The Wiener falter is used for this purpose. But the conventional Wiener filter cannot remove noise well in both edge and smooth region due to the single size estimation window. In addition, it ignores the correlation between pixels. In this paper, we propose a new noise reduction algorithm, in which adaptive estimation window is used according to property of smooth region and edge region. In order to make edge more clear, directional Gaussian mask and directional estimation window combines to the Wiener filter according to direction of edge. From the simulation results, it can be seen that the proposed algorithm showed improves performance in both PSNR arid subjective evaluation