• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.117-123
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• 2013

By calculating the spectral efficiency of symmetric balance incomplete block design(BIBD) codes satisfying BER=$10^{-9}$, it can be found that ideal BIBD code design with m=2 and various q's is effective when effective power is high($P_{sr}=-10$ dBm). But BIBD code design with q > 2 and various m's can be effective when effective power is low($P_{sr}=-25$ dBm).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1319-1335
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• 2017

This paper proposes an opportunistic reporting-based sensing-reporting-throughput optimization scheme that maximizes the spectral efficiency of secondary users (SUs) in cooperative cognitive radio networks with a soft combining rule. The performance of cooperative spectrum sensing depends on the sensing time, the reporting time of transmitting sensing results, and the fusion scheme. While longer sensing time and reporting time improve the sensing performance, this shortens the allowable data transmission time, which in turn degrades the spectral efficiency of SUs. The proposed scheme adopts an opportunistic reporting scheme to restrain the reporting overhead and it jointly controls the sensing-reporting overhead in order to increase the spectral efficiency of SUs. We show that there is a trade-off between the spectral efficiency of SUs and the overheads of cooperative spectrum sensing. The numerical results demonstrate that the proposed scheme significantly outperforms the conventional sensing-throughput optimization schemes when there are many SUs. Moreover, the numerical results show that the sensing-reporting time should be jointly optimized in order to maximize the spectral efficiency of SUs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.672-679
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• 2006

Cognitive radio, which is designed to dynamically adapt its transmission to the environments, is believed to be one of the fundamental techniques for future spectrum utilization. As the first step of cognitive radio, spectrum sensing is treated as the most important technique, through which cognition is well explained. In this paper, we propose a spectral correlation based detection method for spectrum sensing. An unlicensed secondary user system operating in TV broadcast bands is taken as an example. Based on the cyclostationarity of communication signals, spectral correlation function is used to minimize the effect of random noise and interference. Energy measurement and peak detection based criteria are proposed. Simulation results show that the proposed detection method outperforms the energy detection and is more suitable for spectrum sensing in cognitive radios.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.11a
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• pp.23-29
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• 2003

Detection in remotely sensed images can be conducted spatially, spectrally or both [2]. If the images have high spatial resolution, materials can be detected by using spatial and spectral information, unless we can't see the object embedded in a pixel. In this paper, we intend to solve the limit of spatial resolution by using the hyperspectral image which has high spectral resolution. Therefore, the Linear Spectral Mixing(LSM) Model which is sub-pixel detection algorithm is used to solve this problem. To find class Endmembers, we applied Geometric Model with MNF(Minimum Noise Fraction) transformation. From the result of sub-pixel detection algorithm, we can see the detection of water is satisfied and the object shape cannot be extracted but the possibility of material existence can be identified.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.41-47
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• 2006

Detection and identification of targets from remotely sensed imagery are of great interest for civilian and military application. This paper presents an algorithm for target detection in high spatial resolution imagery based on the spectral and the dimensional characteristics of the reference target. In this algorithm, the spectral and the dimensional information of the reference target is extracted automatically from the sample image of the reference target. Then in the entire image, the candidate target pixels are extracted based on the spectral characteristics of the reference target. Finally, groups of candidate pixels which form isolated spatial objects of similar size to that of the reference target are extracted as detected targets. The experimental test results showed that even though the algorithm detected spatial objects which has different shape as targets if the spectral and the dimensional characteristics are similar to that of the reference target, it could detect 97.5% of the targets in the image. Using hyperspectral image and utilizing the shape information are expected to increase the performance of the proposed algorithm.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.322-340
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• 2012

Orthogonal Frequency Division Multiplexing (OFDM) is usually regarded as a spectral efficient multicarrier modulation technique, yet it suffers from a high peak-to-average power ratio (PAPR) problem. Among all the existing PAPR reduction techniques in OFDM systems, side information based PAPR reduction techniques such as partial transmit sequence (PTS) and selective mapping (SLM) schemes, have attracted the most attention. However, the transmission of side information results in somewhat spectral loss and this does not significantly improve the bit error rate (BER) performance. Parallel combinatory (PC) OFDM yields higher spectral efficiency (SE) and better BER performance on Gaussian channels,while is a little but not obvious PAPR improvement over the ordinary OFDM system. This investigation aimed to design a 'perfect' OFDM system. We introduce the side information to rotate the subcarrier phases of our novel PC-OFDM system structure, and call this new system the SIPC(Side information based Parallel Combinatory)-OFDM system. The proposed system achieves better PAPR and SE performance. In addition, considering the tradeoff of system parameters, the proposed system also has the properties of a higher BER.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.556-560
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• 2009

We have investigated the spectral characteristics of semiconductor lasers locked to the external light injected from a modulated laser. study on FM sideband injection locking has shown that when SLs are locked to the target sidebands of the directly modulated ML, the presence of the unselected sidebands influences the resulting microwave signals. The unselected signals can produce the unwanted beat signals around the desired beat signal, which degrade the overall system performance. This analysis way to generate Giga HZ signal generation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.713-718
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• 1987

In this paper, an iterative restoration algorithm from power spectral density with 1 bit sign information of real part of two dimensional Fourier transform of image corrupted by additive white Gaussian noise is proposed. This method is a modified version of image reconstruction algorithm from power spectral density. From the results of computer simulation with original 32 gray level imgae of 64x64 pixels, we can find that restorated image after each iteration converge to original image very fast, and SNR gain be at least 8[dB] after 10th iteration for corrupted image with additive white Gaussian noise.