• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1767-1774
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• 2016

In this paper, we propose the adaptation filtering for correcting the movement path of the recognized object by the depth information. When we recognize the object by the depth information, the path error should be occurred because of the noises in the depth information. The path error is corrected by appling the lowpass filtering, but the lowpass filtering is not efficient when the changes of the object's movement are rapid. In this paper, we apply the adaptation filtering that it gives weights adaptively as the difference between the predicted location and the measured location. To apply the adaptation filtering, we can see that the proposed method can correct accurately the path error of the radical change from simulation results.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.219-225
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• 2013

This paper presents a method using Maximum-Likelihood Linear Regression (MLLR) adaptation to improve recognition performance of Limabeam algorithm for speech recognition using microphone array. From our investigation on Limabeam algorithm, we can see that the performance of filtering optimization depends strongly on the supporting optimal state sequence and this sequence is created by using Viterbi algorithm trained with HMM model. So we propose an approach using MLLR adaptation for the recognition of speech uttered in a new environment to obtain better optimal state sequence that support for the filtering parameters' optimal step. Experimental results show that the system embedded with MLLR adaptation presents the word correct recognition rate 2% higher than that of original calibrate Limabeam and also present 7% higher than that of Delay and Sum algorithm. The best recognition accuracy of 89.4% is obtained when we use 4 microphones with 5 utterances for adaptation.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.285-288
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• 2007

There is substantial evidence from earlier researches that older adults have difficult seeing under low illumination and at night, even in the absence of ocular diseases. During human aging, there is a rampant decrease in rod/cone-meditated adaptation which is caused by delayed rhodopsin regeneration and pigment depletion. This calls for a need to develop appropriate visual gadgets to effectively aid the aging generation. Our research culminates its approach from Pattanaik's model by making extensions to temporal visual filtering, thereby simulating a reduction of visual response which comes with age. Our filtering model paves way and lays a foundation for future research to develop a more effective adaptation model that may be further used in developing visual content adaptation aids and guidelines in MPEG 21 environment. We demonstrate our visual model using a High Dynamic Range image and the experiment results are in conversant with the psychophysical data from previous vision researches.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.69-76
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• 2006

In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.478-481
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• 1996

Tracking a target of versatile maneuver recently demands a stable adaptation of tracker, and the multiple model techniques are being developed because of its ability to produce useful information of target maneuver. This paper presents the way to apply the multiple model method in a moving-target and moving-platform scenario, and the estimation and prediction results better than those of single Kalman filter.

• Structural Engineering and Mechanics
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• v.56 no.3
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• pp.423-442
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• 2015

This study examines the wavelet transform for output-only system identification of ambient excited engineering structures with emphasis on its utilization for modal parameter estimation of high-order and closely-spaced modes. Sophisticated time-frequency resolution analysis has been carried out by employing the modified complex Morlet wavelet function for better adaption and flexibility of the time-frequency resolution to extract two closely-spaced frequencies. Furthermore, bandwidth refinement techniques such as a bandwidth resolution adaptation, a broadband filtering technique and a narrowband filtering one have been proposed in the study for the special treatments of high-order and closely-spaced modal parameter estimation. Ambient responses of a 5-story steel frame building have been used in the numerical example, using the proposed bandwidth refinement techniques, for estimating the modal parameters of the high-order and closely-spaced modes. The first five natural frequencies and damping ratios of the structure have been estimated; furthermore, the comparison among the various proposed bandwidth refinement techniques has also been examined.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.539-548
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• 2007

Mobile content adaptation is a technology of effectively representing the contents originally built for the desktop PC on wireless mobile devices. Previous approaches for Web content adaptation are mostly device-dependent. Also, the content transformation to suit to a smaller device is done manually. Furthermore, the same contents are provided to different users regardless of their individual preferences. As a result, the user has difficulty in selecting relevant information from a heavy volume of contents since the context information related to the content is not provided. To resolve these problems, this paper proposes an enhanced method of Web content adaptation for mobile devices. In our system, the process of Web content adaptation consists of 4 stages including block filtering, block title extraction, block content summarization, and personalization through learning. Learning is initiated when the user selects the full content menu from the content summary page. As a result of learning, personalization is realized by showing the information for the relevant block at the top of the content list. A series of experiments are performed to evaluate the content adaptation for a number of Web sites including online newspapers. The results of evaluation are satisfactory, both in block filtering accuracy and in user satisfaction by personalization.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.6
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• pp.77-87
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• 2007

It will need a quite long time to replace IPv4 protocol, which currently used, with IPv6 protocol completely, thus we will use both IPv4 and IPv6 together in the Internet during the period. For coexisting protocols, IETF standardized various IPv4/IPv6 transition mechanisms. However, new security problems of IPsec adaptation and IPv6 packet filtering can be raised by tunneling mechanism which mainly used in transition mechanisms. To resolve these problems, we suggested two improved schemes for packet filtering functions, which consists of an inner header filtering scheme and a dedicated filtering scheme for IPv4/IPv6 transition mechanisms. Also we implemented our proposed schemes based on Linux Netfilter framework, and we tested their filtering functions and evaluated experimental performance of our implementation on IPv4/IPv6 transition testbed. These evaluation tests indicated that our improved packet filtering functions can solve packet filtering problems of IPv4/IPv6 transition mechanisms without severely affecting system performance.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.944-950
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• 2015

Recent studies on ankle-foot prostheses used for transtibial amputees have focused on the adaptation of the ankle angle of the prosthesis according to ground conditions. For adaptation to various ground conditions (e.g., incline, decline, and step conditions), ankle-foot prostheses should first recognize the ground conditions as well as the current human motion pattern. For this purpose, the ground reaction forces and orientation angle of the tibia provide fundamental information. The measurement of the orientation angle, however, creates a challenge in practice. Although various sensors, such as accelerometers and gyroscopes, can be utilized to measure the orientation angles of the prosthesis, none of these sensors can be solely used due to their intrinsic drawbacks. In this paper, a time-varying complementary filtering (TVCF) method is proposed to incorporate the measurements from an accelerometer and a gyroscope to obtain a precise orientation angle. The cut-off frequency of TVCF is adaptively determined according to the human gait phase detected by a fuzzy logic algorithm. The performance of the proposed method is verified through experiments.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.882-885
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• 2003

In this paper, nonlinear echo cancellation using a correlation LMS (CLMS) algorithm is proposed to cancel the undesired nonlinear echo signals generated in the hybrid system of the telephone network. In the telephone network, the echo signals may result the degradation of the network performance. Furthermore, digital to analog converter (DAC) and analog to digital converter (ADC) may be the source of the nonlinear distortion in the hybrid system. The adaptive filtering technique based on the nonlinear Volterra filter has been the general technique to cancel such a nonlinear echo signals in the telephone network. But in the presence of the double-talk situation, the error signal for tap adaptations will be greatly larger, and the near-end signal can cause any fluctuation of tap coefficients, and they may diverge greatly. To solve a such problem, the correlation LMS (CLMS) algorithm can be applied as the nonlinear adaptive echo cancellation algorithm. The CLMS algorithm utilizes the fact that the far-end signal is not correlated with a near-end signal. Accordingly, the residual error for the tap adaptation is relatively small, when compared to that of the conventional normalized LMS algorithm. To demonstrate the performance of the proposed algorithm, the DAC of hybrid system of the telephone network is considered. The simulation results show that the proposed algorithm can cancel the nonlinear echo signals effectively and show robustness under the double-talk situations.