• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.629-635
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• 2017

In this paper, we proposed a nonlinear synthesis filter for noise reduction to reduce the effects of Gaussian noise and impulse noise. When the centralization of the local mask is judged to be Gaussian noise by the noise judgment, the weight value of the weight filter are applied differently according to the spatial weight filter and the pixel change by using the sample variance in the local mask. And if it is determined as the impulse noise, we proposed an algorithm that applies different weights of local histogram weight filter and standard median filter according to noise density of mask. In order to evaluate the performance of the proposed filter algorithm, we used PSNR(peak signal to noise ratio) and compared existing methods and proposed filter algorithm in the mixed noise environment with Gaussian noise, impulsive noise, and two noises mixed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3507-3522
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• 2022

Model pruning methods have attracted huge attention owing to the increasing demand of deploying models on low-resource devices recently. Most existing methods use the weight norm of filters to represent their importance, and discard the ones with small value directly to achieve the pruning target, which ignores the contribution of the small norm filters. This is not only results in filter contribution waste, but also gives comparable performance to training with the random initialized weights [1]. In this paper, we point out that the small norm filters can harm the performance of the pruned model greatly, if they are discarded directly. Therefore, we propose a novel filter contribution recycle (FCR) method for structured model pruning to resolve the fore-mentioned problem. FCR collects and reassembles contribution from the small norm filters to obtain a mixed contribution collector, and then assigns the reassembled contribution to other filters with higher probability to be preserved. To achieve the target FLOPs, FCR also adopts a weight decay strategy for the small norm filters. To explore the effectiveness of our approach, extensive experiments are conducted on ImageNet2012 and CIFAR-10 datasets, and superior results are reported when comparing with other methods under the same or even more FLOPs reduction. In addition, our method is flexible to be combined with other different pruning criterions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.911-913
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• 2013

The user's context awareness is important to the reliability of sensors data. The sensor data is constantly change to external temp, internal& external environment and vibration. This noise environment is affecting that the data collected information from sensors. Of course this method of digital filter and inference algorithm specifically request for the use of ripple noise and action inference. In this paper, experiment was a comparison of the KF(Kalman Filter) and WMAF(Weight Moving Average Filter) for noise decrease and distortion prevention according to user behavior. And, we compared the EWDF(Extended Weight Dual Filter) with several filer. In an experiment, in contrast to other filter, the proposed filter is robust in a noise-environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3534-3553
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• 2021

The low cost of Bluetooth technology has led to its wide usage in indoor positioning. However, some inherent shortcomings of Bluetooth technology have limited its further development in indoor positioning, such as the unstable positioning state caused by the fluctuation of Received Signal Strength Indicator (RSSI) and the low transmission frequency accompanied by a poor real-time performance in positioning and tracking moving targets. To address these problems, an indoor fusion positioning algorithm of Bluetooth technology and pedestrian dead reckoning (PDR) based on a particle filter with dynamic adjustment of weights calculation strategy (BPDW) will be proposed. First, an orderly statistical filter (OSF) sorts the RSSI values of a period and then eliminates outliers to obtain relatively stable RSSI values. Next, the Group-based Trilateration algorithm (GTP) enhances positioning accuracy. Finally, the particle filter algorithm with dynamic adjustment of weight calculation strategy fuses the results of Bluetooth positing and PDR to improve the performance of positioning moving targets. To evaluate the performance of BPDW, we compared BPDW with other representative indoor positioning algorithms, including fingerprint positioning, trilateral positioning (TP), multilateral positioning (MP), Kalman filter, and strong tracking filter. The results showed that BPDW has the best positioning performance on static and moving targets in simulation and actual scenes.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.10
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• pp.905-911
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• 2014

A Loss-in-Weight (LIW) feeder, a type of automated measuring device, is a continuous feeder used in many mass production industries. Due to its versatility, there have been constant demands of LIW feeders in food production supply lines as well as chemical and pharmaceutical industries. In this paper, the process of designing a LIW feeder system with better performance will be examined and compared with commercial products. This system is characterized by low pass Butterworth filter and feed forward PI control. The filter is for noise disposal caused by dynamic condition of a LIW feeder. The feed forward PI control, based on linearity feature of feeders, is adequate for stable driving of the system. At the end, a possible evaluation method of LIW system will be proposed to verify the specific achievement of this paper.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.81-89
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• 1999

Image obtained by incomplete communication always include noise, blur and distortion, etc. In this paper, we propose and apply the new spatial filter algorithm, called an optimal adaptive generalized stack filter(AGSF), which optimizes adaptive generalized stack filter(AGSF) using neural network weight learning algorithm of back-propagation learning algorithm for improving noise removal and edge preservation rate. AGSF divides into two parts: generalized stack filter(GSF) and adaptive multistage median filter(AMMF), GSF improves the ability of stack filter algorithm and AMMF proposes the improved algorithm for reserving the sharp edge. Applied to neural network theory, the proposed algorithm improves the performance of the AGSF using two weight learning algorithms, such as the least mean absolute(LAM) and least mean square (LMS) algorithms. Simulation results of the proposed filter algorithm are presented and discussed.

• Journal of the Korean Society of Tobacco Science
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• v.23 no.2
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• pp.179-184
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• 2001

This study was conducted to determine the smoke component distribution and the relationship between chemical components and physical characteristics of cigarettes. 16 different cigarette brands which were sold in the market were selected for this study. Five kinds of smoke components which have been tar, nicotine, water, carbon monoxide(CO) puff No., and six kinds of physical characteristics which were filter type, leaf weight, filter weight, UPD, EPD, dilution rate were analyzed. The average values in tar, nicotine, water, CO concentration were 6.5 mg/cig. 0.66 mg/cig, 1.12 mg/cig. and 6.32 mg/cig., respectively. The average ratios of nicotine/tar and CO/tar were 0.10, and 1.02 respectively. The distribution of smoke components collected in the cambridge filter and cigarette filter was different. The averages of tar and nicotine removal efficiency by a cigarette filter were 53%, and 48%, respectively. All smoking components were positively correlated with other smoking components. filter types, EPD, and dilution rate were showed high correlation to the changes of smoke components. Especially, dilution rate of cigarette strongly affected on the changes of all smoke components.

• Plant Resources
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• v.7 no.1
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• pp.77-86
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• 2004

The reduced ratio of red:far-red (R:FR) light acts as a measure of the proximity of competitors and plants can detect the potentially competing neighbor plants by perceiving reflected R:FR signals and initiate the response of “shade avoidance” before actual shading occurs. The phytochrome system is responsible for monitoring the changes in the R:FR and initiating the shade avoidance response. The response to low R:FR ratio was studied in a white aspen Populus alba clone ‘Bolleana’ using two filter systems: a clear plastic filter system that allows a R:FR ratio less than 1.0 to pass from adjacent border plant reflection; and a special commercial plastic that blocks FR light and creates a R:FR ratio above 3.0. The reduced R:FR signals enhanced the stem elongation in response to competition at the expense of relative stem diameter growth. Trees grown inside clear chambers were 27 ％ taller than trees grown inside the FR-blocking filter chambers. Stem taper of clear chamber trees was 16％ less than the FR-blocking filter trees. Low R:FR also induced 22％ more stem dry weight and 13％ greater petiole length per leaf compared to the FR-blocking filter trees. There were no statistically significant differences in leaf area, leaf number increment, and total dry weight between the two light filter treatments.