• Journal of the Semiconductor & Display Technology
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• v.6 no.3
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• pp.55-59
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• 2007

Wavelet Transform is amenable to efficient algorithms. So wavelet transform was adopted many signal processing and communication applications. For example, the wavelet transform was adopted as the transform for JPEG2000. However, Wavelet has weakness about smoothness along the contours and limited directional information. Hence, recently, some new transforms have been introduced to take advantage of this property. So we use to other transform, called contourlet transform in compression. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. Contourlet transform has a good result about images with smooth contours. Moreover, Contourlet is feasible multiresolution and multidirection expansion using non-separable filter bank. This treatise shows a good image representation after compressing using contourlet transform.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.2063-2066
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• 2002

In this paper, we propose a structure far lossless audio coding method. Prediction model is used in the wavelet transform domain. After DWT, wavelet coefficients is quantized and decorrelated by prediction modeling. The DWT can be constructed to critical bands. We can get a lower data rate representation of audio signal which has a good quality like the result of perceptual coding. Then the prediction errors are efficiently coded by the Golomb-coding method. The prediction coefficients are fixed for reducing the computational burden when we find prediction coefficients.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.282-285
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• 2000

Three representations are known to implement the discrete wavelet transform (DWT) ; i.e., direct, lifting and matrix forms. In these representations, direct and lifting forms are well known so far. This paper derives the matrix form of the DWT from the direct form. Then, we implement these three representations on a programmable digital signal processor (in the following, DSP processor) and compare them in terms of the number of calculations and instruction cycles. As a result, we confirm that the lifting form has the lowest number of calculations and cycles, and the matrix form has an effective decrease in the number of cycles than other representations on the DSP processor.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.73-79
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• 2005

This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2525-2527
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating, so it is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• ETRI Journal
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• v.29 no.5
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• pp.619-632
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• 2007

Side channel attacks are a very serious menace to embedded devices with cryptographic applications. To counteract such attacks many randomization techniques have been proposed. One efficient technique in elliptic curve cryptosystems randomizes addition chains with binary signed digit (BSD) representations of the secret key. However, when such countermeasures have been used alone, most of them have been broken by various simple power analysis attacks. In this paper, we consider combinations which can enhance the security of countermeasures using BSD representations by adding additional countermeasures. First, we propose several ways the improved countermeasures based on BSD representations can be attacked. In an actual statistical power analysis attack, the number of samples plays an important role. Therefore, we estimate the number of samples needed in the proposed attack.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.89-92
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• 2001

For the diagnosis of arrhythmia in the heart system, the QRS complex of ECG signals is used in many cases. The rejection of the noise in ECG signals is important to acquisition of exact QRS complex. This paper presents some experimental results about instantaneous bandwidth estimation and noise rejection of ECG signals with the purpose of rejection of the 60 Hz power noise and the motion artifacts such as EMG signals and contact noise. ECG signals corrupted by noise are cleaned by using the variable bandwidth filter. For the filtering of ECG signals with noise, the instantaneous bandwidth of the signals is estimated by analysis of time-frequency representation of ECG signal.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.331-341
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• 1991

The discrete cosine transform (DCT) is widely used in many signal processing areas, including image and speech data compression. In this paper, we investigate a fixed-point error analysis for fast DCT algorithms, namely, Lee [6], Hou [7] and Vetterli [8]. A statistical model for fixed-point error is analyzed to predict the output noise due to the fixed-point implementation. This paper deals with two's complement fixed-point data representation with truncation and rounding. For a comparison purpose, we also investigate the direct form DCT algorithm. We also propose a suitable scaling model for the fixed-point implementation to avoid an overflow occurring in the addition operation. Computer simulation results reveal that there is a close agreement between the theoretical and the experimental results. The result shows that Vetterli's algorithm is better than the other algorithms in terms of SNR.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3150-3152
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• 1999

The efficient representation and encoding of signals with limited resources, e.g., finite storage capacity and restricted transmission bandwidth, is a fundamental problem in technical information processing systems. Typically under realistic circumstances, the encoding and communication of message has to deal with different sources of noise and disturbances. In this paper, I propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, and random elimination of prototypes. The resulting algorithm is able to limit the detrimental effect of noise in a very general communication scenario. In this paper, based on the robust vector quantization I have an experiment about speech coding.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3224-3226
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• 1999

This paper introduces a nonlinear wavelet transform based on the lifting scheme, which is applied to signal denoising through the translation invariant wavelet transform. The wavelet representation using orthogonal wavelet bases has received widespread attention. Recently the lifting scheme has been developed for the construction of biorthogonal wavelets in the spatial domain. In this paper, we adaptively reduce the vanishing moments in the discontinuities to suppress the ringing artifacts and this customizes wavelet transforms providing an efficient framework for the translation invariant denoising. Special care has been given to the boundaries, where we design a set of different prediction coefficients to reduce the prediction error.