• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.243-246
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• 2003

In this paper, we propose a new digital audio watermarking technique with the wavelet transform. The watermark is embedded by eliminating unnecessary information of audio signal based on human auditory system (HAS). This algorithm is an audio watermarking method, which does not require any original audio information in watermark extraction process. In this paper, the masking effect is used for audio watermarking, that is, post-tempera] masking effect. We construct the window with the synchronization signal and we extract the best frame in the window by using the zero-crossing rate (ZCR) and the energy of the audio signal. The watermark may be extracted by using the correlation of the watermark signal and the portion of the frame. Experimental results show good robustness against MPEG1-layer3 compression and other common signal processing manipulations. All the attacks are made after the D/A/D conversion.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1578-1581
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• 2002

In this paper, the accuracy of the direction-of-arrival (DOA) estimation of signal impinged on the uniform linear array (ULA) is investigated. The conventional beamformer and Capon’s beamformer categorized in beamformaing techniques as well as MUSIC (MUlti-pie Signal Classification) and ESPRIT (Estimation of Signal Invariance Techniques) categorized in subspace- based methods are employed to estimate the DOAs. From the simulation result under uncorrelated environment, MUSIC can prominently distinguish the DOAs while the beamforming techniques cannot demonstrate the DOAs as clear as MUSIC does. Moreover, Uni-tary ESPRIT is employed to estimate the DOAs under uncorrelated signal conditions. By means of Uni-tary ESPRIT, the estimation has more accuracy with the computational-time reduction. In addition, it incorporates forward-backward averaging; thus Unitary ES-PRIT can overcome the problem of the coherent signal condition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.60-67
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• 2009

The phase retrieval problem is a problem of reconstructing a signal or the phase of Fourier transform of the signal from the magnitude of its Fourier transform. In this paper we address the problem of reconstructing an unknown signal from the magnitude of its Fourier transform and the magnitude of Fourier transform of another signal that is given by the addition of the desired signal. After we briefly mention the uniqueness conditions under which a signal can be uniquely specified from the given information and key equations of the iterative algorithm, we present mathematical background that the iterative algorithm converges to the desired signal, present an example that illustrates the performance of the reconstruction algorithm, and show its convergence property.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.551-555
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• 2009

This paper proposes a signal generation method for automatic control of a monitoring camera. Using the control signal, the monitoring camera can track a moving object and keep it near the image center for a longer time. The proposed method is estimated in the experiments that automatically move a maker located at the specified position to the image center.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.419-426
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• 1998

The information for operating the train should be transmitted to train, with extreme security. In our system, The information, such that the allowable velocity of the train, train existence in current area, and other data necessary for operating train, is transmitted in the form of FM signal. Received by the receiver located on train, the signal is filtered, demodulated, and analyzed for extracting the original information. The analysis of the demodulated signal is done through FFT algorithm using sliding slot. The simulation results shows the validity of the algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.4
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• pp.318-324
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• 2013

For blind channel equalization, the reliability of signal estimate determines the convergence speed and steady-state performance of the equalizer. Therefore the nonlinear estimator and reference signal being used in signal estimate should be chosen appropriately. In this paper, to increase the reliability of the signal estimate, two errors were obtained by applying coarse signal points and dense signal points respectively to signal estimate, the relative reliabilities of two errors were calculated, then the equalizer was adapted deferentially utilizing the reliabilities. At this point, by applying two errors alternately, two modes of operation were smoothly combined. Through computer simulations the proposed method was confirmed to achieve fast transient state convergence and low steady-state error compared to traditional methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.7
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• pp.786-795
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• 2010

In this paper, we propose a new EBG structure that the two unit cells are connected by the bridge line in signal transmission plane. The SSN of the power plane is reduced effectively by via holes and bridge lines connecting the unit cells. The superior signal transfer characteristic is shown between the signal lines in the signal transmission plane. The proposed EBG structure contains 1.2 GHz cut-off frequency and less than －30 dB suppression in the 8.3 GHz broad bandwidth. In addition, To improve the SI(Signal Integrity) in signal transmission plane keeping the same bandstop frequency range, the optimized location of the reference plane is proposed.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.223-228
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• 2003

In this paper, we introduce a hyper-chaos secure communication method using hyper-chaos circuit onsist of State-Controlled Cellular Neural Network SC-CNN). We make a hyper-chaos circuit using SC-CNN with the n-double scroll or Chua's oscillator. A hyper-chaos circuit is created by applying identical n-double scroll or non-identical n-double scroll and Chua's oscillator with weak coupled method to each cell. Hyper-chaos ynchronization was achieved using GS (Generalized Synchronization) method between the transmitter and receiver about each state variable in the SC-CNN. In order to secure communication, we have synthesizing the desired information with a hyper-chaos circuit by adding the information signal to the hyper-chaos signal using the SC-CNN in the transmitter. And then, transmitting the synthesized signal to the ideal channel, we confirm secure communication by separating the information signal and the hyper-chaos signal in the receiver.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1926-1945
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• 2014

In this paper, we propose a distributed signal subspace interference alignment algorithm for single beam K-user ($3K{\geq}$) MIMO interference channel based on sum rate maximization and game theory. A framework of game theory is provided to study relationship between interference signal subspace and altruistic-egoistic bayesian game cost function. We demonstrate that the asymptotic interference alignment under proposed scheme can be realized through a numerical algorithm using local channel state information at transmitters and receivers. Simulation results show that the proposed scheme can achieve the total degrees of freedom that is equivalent to the Cadambe-Jafar interference alignment algorithms with perfect channel state information. Furthermore, proposed scheme can effectively minimize leakage interference in desired signal subspace at each receiver and obtain a moderate average sum rate performance compared with several existing interference alignment schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2028-2041
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• 2019

Compressed sensing (CS) is a new theory. With regard to the sparse signal, an exact reconstruction can be obtained with sufficient CS measurements. Nevertheless, in practical applications, the transform coefficients of many signals usually have weak sparsity and suffer from a variety of noise disturbances. What's worse, most existing classical algorithms are not able to effectively solve this issue. So we proposed an efficient algorithm based on smoothed ${\ell}_0$ norm for sparse signal reconstruction. The direct ${\ell}_0$ norm problem is NP hard, but it is unrealistic to directly solve the ${\ell}_0$ norm problem for the reconstruction of the sparse signal. To select a suitable sequence of smoothed function and solve the ${\ell}_0$ norm optimization problem effectively, we come up with a generalized approximate function model as the objective function to calculate the original signal. The proposed model preserves sharper edges, which is better than any other existing norm based algorithm. As a result, following this model, extensive simulations show that the proposed algorithm is superior to the similar algorithms used for solving the same problem.