• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.123-130
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• 1996

Due to high payload capacity and high length-to -cross-section ratio requirements, long-reach manipulator systems are expected to exhibit significant structural flexibility. To avoid structural vibrations during operations, various types of input shaping filtering methods have been investigated. A robust notch filtering method and an impulse shaping filtering method were investigated and implemented. In addition, two very different approaches have been developed and compared. One new approach, referred to as a

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.183-190
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• 2012

Mobile web applications are different from desktop web applications because of their small screen size and small user input devices. Therefore user interface designers have spent their effort and time to re-design the user interface of mobile web applications to meet these differences. In this paper, we introduce five user interface patterns for mobile web applications to reduce their effort and time. Two of them are for utilizing small screen size efficiently, and they are space overloading pattern and data filtering pattern. These patterns enable designers to reduce screen usage. The other three patterns - data suggestion pattern, input reuse pattern, and incremental data input pattern - are for helping users' data input on mobile devices. These three patterns enable users to reduce direct data input. Our work will help user interface designers develop mobile web interface to utilize screen space efficiently and get data with less errors and less efforts from users.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.26-33
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• 1992

This paper presents lattice structure of bilinear filter and the conversion equations from lattice parameters to direct-form parameters. Billnear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients required. The lattice filter formulation transforms the nonlinear filtering problem into an equivalent multichannel linear filtering problem and then uses multichannel lattice filtering algorithms to solve the nonlinear filtering problem. The lattice filters perform a Gram-Schmidt orthogonalization of the input data and have very good easily extended to more general nonlinear output feedback structures.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.42-46
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• 2002

In this paper, a new pre-processing algorithm is proposed to improve the performance of stereo acoustic echo canceller. The proposed algorithm has the improved performance by the estimation error reduction of filter coefficient using input signal which was reduced reverberation of room in the basis MINT (Mu1tip1e-input/output Inverse Theorem) filtering. For real stereo speech signal and real room impulse response the results of simulation, we showed that the proposed method could improved 3∼5 dB ERLE (Echo Return Loss Enhancement) regardless of NLMS (Normalized Least Mean Square) and Projection adaptive algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.445-453
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• 2001

The multiple targets tracking problem has been one of the main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimen-sion filter, input estimation filter, interacting multiple model(IMM) filter, dederated variable dimension filter with input estimation, etc., have proposed to address the tracking and sensor fusion issues. In this pa- per, two existing tracking algorithm, i.e, the IMM filter and the variable dimension filter with input estima-tion(VDIE), are combined for the purpose of improving the tracking performance for maneuvering targets. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns, i.e., waver, pop-up, and high-diver motions, are defined and are applied to the modified IMM filter as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMM filter than the standard IMM filter are demonstrated though computer simulations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.10-21
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• 1993

Bilinear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients compared with Volterra models. But bilinear filters have stability problem because they involve nonlinear feedback. Adaptive algorithms for bilinear filters may be diverge and have poor convergence characteristics when input signal is large In this paper, necessary and sufficient condition for mean square stability of bilinear filters for given input signal statistics is briefly described, and the method obtaining the input bound to guarantee the stability of bilinear filters is presented. New RPEM algorithm, which does not diverge and has the superior convergence characteristics compared with the conventional RPEM algorithm when input signal is large, is derived by applying the time-varying Kalman filtering concept to the conventional RPEM algorithm.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.45-55
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• 1999

In this paper, we used the WLMS(Wavelet domain Least Mean Square) adaptive filter based on the wavelet transform to cancel grain noise. Usually, grain noise occurs in changes of the crystalline structure of metals in high temperature environment. It makes the detection of flaw difficult. The WLMS adaptive filtering algorithm establishes the faster convergence rate by orthogonalizaing the input vector of adaptive filter as compared with that of LMS adaptive filtering algorithm in time domain. We implemented the WLMS adaptive filter by using the delayed version of the primary input vector as the reference input vector and then implemented the CA-CFAR(Cell Averaging- Constant False Alarm Rate) threshold estimator. CA-CFAR threshold estimator enables to detect the flaw and back echo signals automatically. Here, we used the output signals of adaptive filter as its input signal. To Cow the statistical characteristic of ultrasonic signals corrupted by grain noise, we performed run test. The results showed that ultrasonic signals are nonstationary signal, that is, signals whose statistical properties vary with time. The performance of each filter is appreciated by the signal-to-noise ratio. After LMS adaptive filtering in time domain, SNR improves to about 2-3㏈ but after WLMS adaptive filtering in wavelet domain, SNR improves to about 4-6㏈.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.4
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• pp.1-7
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• 2009

In this paper, the author presents the MIMO(Multi-Input Multi-Output) receiver algorithm with the capability of inter-cell or inter-sector interference cancellation over multi-antenna OFDM(Orthogonal Frequency Division Multiplexing) systems. As contrast with the previous research dealing with the filtering scheme at the time domain, the proposed algorithm is presented as the pre-filtering scheme which can be applicable to the frequency domain. Note that the proposed one can be implemented only by pilot symbols which are used in the channel estimation. In addition, it is analytically confirmed that the proposed scheme can be applied for either MIMO( C-SM(Collaborative-Spatial Multiplexing)) interference or SIMO(Single-Input Multi-Out) interference. The proposed receiver algorithm is verified by simulations over UL-PUSC SR off in IEEE 802.16e standard. From simulation results, it is confirmed that the proposed one can be applicable regardless of the kind of interference. Furthermore, it is verified that the performance is guaranteed even under Ole severe effect of interference and the improvement of system throughput is guaranteed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.