• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.47-52
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• 1998

This paper prolposes a VFM (Variable Fading Memory)Kalman filtering and applies it to the parameter estimation for time-varying signals. By adaptively calculating the fading memory, the proposed algorithm does not require any predetermined fading memory when estimating the time-varying signal parameter. Moreover, the proposed algorithm has faster convergence speed than fixed fading memory one in case the signal contains an impulsive outlier. The performance of parameter estimation for time-varying signal is evaluated by computer simulation for two cases, one of which is the chirp signal whose frequency varies linearly with time and the other is the chip signal with an impulsive outlier. The experimental results show that the VFM Kalman filtering estimates the parameter of the chirp signal more rapidly than the fixed fading memory one in the region of an outlier.

• MALSORI
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• no.51
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• pp.85-98
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• 2004

It is almost impossible to generate the sound field effect in real time with the time-domain linear convolution because of its large multiplication operation requirement. To solve this, three methods are introduced to reduce the number of multiplication operations in this paper. Firstly, the time-domain linear convolution is replaced with the frequency-domain circular convolution. In other words, the linear convolution result can be derived from that of the circular convolution. This technique reduces the number of multiplication operations remarkably, Secondly, a subframe concept is introduced, i.e., one original frame is divided into several subframes. Then the FFT is executed for each subframe and, as a result, the number of multiplication operations can be reduced. Finally, the QFT is used in stead of the FFT. By combining all the above three methods into our final the SFE generation algorithm, the number of computations are reduced sufficiently and the real-time SFE generation becomes possible with a general PC.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.679-687
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• 2009

In this paper, a subband filtering and adaptive prediction technique for analyzing harmonics in power systems is presented. In this method, the filter banks are designed to decompose odd and even order harmonics separately. The adaptive prediction has been employed reduce the transient and white noise effect in time varying harmonics detecting and tracking. The frequencies and amplitudes of the decomposed harmonics are estimated by recursive algorithm. To demonstrate the performances of the developed technique, computer simulations to the signal with the time-varying frequency and THD are carried out.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.18-26
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• 2011

This paper presents a method, Exposure Controlled Temporal Filtering (ECF), applied to visual motion tracking, that can cancel the temporal aliasing of periodic vibrations of cameras and fluctuations in illumination through the control of exposure time. We first present a theoretical analysis of the exposure induced image time integration process and how it samples sensor impingent light that is periodically fluctuating. Based on this analysis we develop a simple method to cancel high frequency vibrations that are temporally aliased onto sampled image sequences and thus to subsequent motion tracking measurements. Simulations and experiments using the 'Center of Gravity' and Normalized Cross-Correlation motion tracking methods were performed on a microscopic motion tracking system to validate the analytical predictions.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.85-96
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• 2020

It is important to extract salient object image and to solve the invariance problem for image recognition. In this paper we propose a new hybrid algorithm for invariance and improved classification performance in image recognition, whose algorithm is combined by FT(Frequency-tuned Salient Region Detection) algorithm, Guided filter, Zernike moments, and a simple artificial neural network (Multi-layer Perceptron). The conventional FT algorithm is used to extract initial salient object image, the guided filtering to preserve edge details, Zernike moments to solve invariance problem, and a classification to recognize the extracted image. For guided filtering, guided filter is used, and Multi-layer Perceptron which is a simple artificial neural networks is introduced for classification. Experimental results show that this algorithm can achieve a superior performance in the process of extracting salient object image and invariant moment feature. And the results show that the algorithm can also classifies the extracted object image with improved recognition rate.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.10a
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• pp.82-87
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• 1984

A 2-D digital filter with rational frequency response can be expanded into an infinite sequence of filterins operations. Each filtering operation can be implemented by convolution with a Low-order 20D finite-extent impulse response. If a convergence constraint is satisfied, the sequence of estimates will approach the desired output signal. In practice, as the number of iterations is finite, the frequency response implemented by iterative computations is an approximation to the desired rational frequency response.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.477-480
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• 2006

To represent the accurate feature of signal and system, many researches have been done in many fields of basic and engineering science which led a great development of modem society. Even until currently, in order to acquire useful information from signals at high speed, many methods and transforms have been processed. In these methods, the Fourier transform which represents signal as the combination of the frequency component has been applied to the most fields. But as transform not to consider time information, the Fourier transform does not provide time information of the time and presents only overall features of signals. The wavelet transform, which is proposed to overcome this problem and recently expands the range of the application, presents time-frequency localization and many kinds of the wavelet can be applied according to the environment of application. In this paper, we detect the features of signals using the function which is considered as the wavelet and do research for filtering locally in the wavelet plane.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.32-37
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• 2010

The algorithm of multiple channel signal processing requires the flexibility of variable frequency band, efficient allocation of transmission power, and flexible frequency band reallocation to satisfy various service types which requires different transmission rates and frequency band. There are three methods including per-channel approach, multiple tree approach, and block approach performing frequency band reallocation method by channelization and dechannelization in the multiple-channel signal. This paper proposes an improved per-channel approach for converting the frequency band of multiple carrier signals efficiently. The proposed algorithm performs decimation and interpolation using CIC(cascaded integrator comb filter), half-band filter, and FIR filter. In addition, it performs filtering of each sub-channel, and reallocates channel band through FIR low-pass filter in the multiple-channel signal. The computer simulation result shows that the perfect reconstruction of output signal and the flexible frequency band reallocation is performed efficiently by the proposed algorithm.

• Journal of electromagnetic engineering and science
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• v.9 no.2
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• pp.98-104
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• 2009

An InGaP/GaAs MMIC LC VCO designed with Harmonic Noise Frequency Filtering(HNFF) technique is presented. In this VCO, internal inductance is found to lower the phase noise, based on an analytic understanding of phase noise. This VCO directly drives the on-chip double balanced mixer to convert RF carrier to IF frequency through local oscillator. Furthermore, final power performance is improved by output amplifier. This paper presents the design for a 1.721 GHz enhanced LC VCO, high power double balance mixer, and output amplifier that have been designed to optimize low phase noise and high output power. The presented asymmetric inductance tank(AIT) VCO exhibited a phase noise of -133.96 dBc/Hz at 1 MHz offset and a tuning range from 1.46 GHz to 1.721 GHz. In measurement, on-chip down-converter shows a third-order input intercept point(IIP3) of 12.55 dBm, a third-order output intercept point(OIP3) of 21.45 dBm, an RF return loss of -31 dB, and an IF return loss of -26 dB. The RF-IF isolation is -57 dB. Also, a conversion gain is 8.9 dB through output amplifier. The total on-chip down-converter is implanted in 2.56${\times}$1.07 mm$^2$ of chip area.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.239-245
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• 2013

In this paper, we propose a time-frequency domain reflectometry (TFDR) based measurement method for localizing concentric neutrals corrosion on live underground power cable. It consists of two inductive couplers which can transmit the reference signal into live underground power cable and measure the reflected signals from the impedance discontinuities of concentric neutrals corrosion. In order to compensate the dispersion of the measured reflected signal via inductive coupler, an equalizer based on Wiener filtering is designed. To improve the localizing performance of concentric neutrals corrosion in the vicinity of the measurement point, the reference signal is removed from the measured reflected signals. The localization performance of the proposed method is verified by the concentric neutrals corrosion localization experiment.