• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.347-352
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• 2016

This paper investigates the application, design and implementation of unscented Kalman filter observer using the various scaling parameters for the sensorless speed control of a permanent magnet synchronous motor. The principles of unscented transformation and unscented Kalman filter are examined and their applications are explained. Typically the mapping transformation process is divided into two types, namely the basic unscented transformation and the general unscented transformation by virtue of the scaling parameter value. And resultantly, the number of sampling points, weights, code configuration and computation time are different. But there is no little information on the scaling parameter value or how this value influences the system performance. To analyze the unscented transformation with the various scaling parameters in this study, the experimental results under a wide range of operation condition have been demonstrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1280-1287
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• 2006

We propose a modified stochastic gradient-based (MSGB) filter showing that the filter is the solution to an optimization problem. This paper analyzes the properties of the MSGB filter that corresponds to the nonlinear adaptive filter with additional update terms, parameterized by the variable scaling factor. The variably parameterized MSGB filter plays a role iii connecting the fixed parameterized MSGB filter and the null parameterized MSGB filter through variably scaling parameter. The stability regions and misadjustments are shown. A system identification is utilized to perform the computer simulation and demonstrate the improved performance feature of the MSGB filter.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.507-511
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• 2010

In this paper, we propose to enhance the performance of software transcoder by using GPGPU for scaling filters. Video transcoding is a technique that translates a video file to another video file that has a different coding algorithm and/or a different frame size. Its demand increases as more multimedia devices with different specification coexist in our daily life. Since transcoding is computationally intensive, a software transcoder that runs on a CPU takes long processing time. In this paper, we achieve significant speed-up by parallelizing the scaling filter using a GPGPU that can provide significantly large computation power. Through extensive experiments with various video scripts of different size and with various scaling filter options, it is verified that the enhanced transcoder could achieve 36% performance improvement in the default option, and up to 101% in a certain option.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.1
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• pp.27-35
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• 1987

Digital filter suffer from roundoff noise and adder overflows due to finite word length effects. Scaling is an attempt to internal signal levels such that all signals are as large as possible, yet without the occurrence of overflows. Scaling requirements are implemented by the use of transformer. This paper proposes a procedure for scaling wave digital filters to avoid overflow problems and at the same time maximizing the output signal-to-noise ratio. Results indicate that the scaled networks have an improved signal to noise ratio over th unscaled filters under the condition that there be no overflow occuring.

• International Journal of Contents
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• v.9 no.3
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• pp.9-14
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• 2013

In this paper, we will examine single face tracking algorithms with scaling function in a mobile device. Face detection and tracking either in PC or mobile device with scaling function is an unsolved problem. Standard single face tracking method with particle filter has a problem in tracking the objects where the object can move closer or farther from the camera. Therefore, we create an algorithm which can work in a mobile device and perform a scaling function. The key idea of our proposed method is to extract the average of skin color in face detection, then we compare the skin color distribution between the detected face and the tracking face. This method works well if the face position is located in front of the camera. However, this method will not work if the camera moves closer from the initial point of detection. Apart from our weakness of algorithm, we can improve the accuracy of tracking.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.3
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• pp.87-92
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• 2008

In this paper, certain scaling functions are generated using the dyadic subband tree structure and applied to a time-hopping, pulse position modulation, ultra-wideband (TH-PPM UWB) system. Scaling functions can be obtained by iterating a lowpass filter at each level using a critically sampled dyadic tree. The performance of the TH-PPM UWB system employing scaling functions as the mono-cycle waveform is evaluated through computer simulations in a Rayleigh fading environment.

• Journal of electromagnetic engineering and science
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• v.11 no.2
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• pp.105-112
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• 2011

In phase-locked frequency synthesizers, a fast-lock technique is frequently employed to overcome the trade-off between a lock-time and a spurious response. The function of fast-lock in a conventional PLL (Phased Lock Loop) IC (Integrated Circuit) is limited by a factor of 16, which is usually implemented by a scaling of charge pumper, and consequently a lock time improvement of a factor of 4 is possible using the conventional PLL IC. In this paper, we propose a novel external active fast-lock loop filter. The proposed loop filter provides, conceptually, an unlimited scaling of charge pumper current, and can overcome conventional trade-off between lock-time and spur suppression. To demonstrate the validity of our proposed loop-filter, we fabricated an X-band frequency synthesizer using the proposed loop filter. The loop filter in the synthesizer is designed to have a loop bandwidth of 100 kHz in the fast-lock mode and a loop bandwidth of 5 kHz in the normal mode, which corresponds to a charge pumper current change ratio of 400. The X-band synthesizer shows successful performance of a lock-time of below 10 ${\mu}sec$ and reference spur suppression below -64 dBc.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.174-180
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• 2016

This paper study about an unscented Kalman filter with a variety type of unscented transformation to estimate state values for speed control without position sensor of a permanent-magnet synchronous motor. The principles of an unscented transformation and unscented Kalman filter are examined and their application is explained. Generally the mapping process can be divided into two type, such as a basic and a general form according to a scaling parameter. And computation time, the number of samples, and weights about samples are different from each other. But, there is no little information on the scaling parameter value how this value influences the system performance. Simulation and experimental results show the validity of the designed unscented transformation performance with the various scaling parameter values for sensorless motor drive.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.107-108
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• 2007

In this paper, a cosine-modulated filter bank with a modified synthesis part is proposed for arbitrary scaling of images, whereby down/up-sampling kernels based on a compactly supported sampling function (CSSF) are utilized. Also, an optimized adaptive interpolation technique is incorporated into the filter bank structure to compensate for quality degradation arising in scaled images. Finally, simulation results verify that high quality images with arbitrary sizes can be obtained by applying the proposed approach.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.