• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.58-78
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• 2016

Compressed sensing (CS) possesses the potential benefits for spectrum sensing of wideband signal in cognitive radio. The sparsity of signal in frequency domain denotes the number of occupied channels for spectrum sensing. This paper presents a scheme of adaptively adjusting the number of compressed measurements to reduce the unnecessary computational complexity when priori information about the sparsity of signal cannot be acquired. Firstly, a method of sparsity estimation is introduced because the sparsity of signal is not available in some cognitive radio environments, and the relationship between the amount of used data and estimation accuracy is discussed. Then the SNR of the compressed signal is derived in the closed form. Based on the SNR of the compressed signal and estimated sparsity, an adaptive algorithm of adjusting the number of compressed measurements is proposed. Finally, some simulations are performed, and the results illustrate that the simulations agree with theoretical analysis, which prove the effectiveness of the proposed adaptive adjusting of compressed measurements.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1083-1096
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• 2021

Compressed sensing-based matching pursuit algorithms can estimate the sparse channel of massive multiple input multiple-output systems with short pilot sequences. Although they have the advantages of low computational complexity and low pilot overhead, their accuracy remains insufficient. Simply multiplying the weight value and the estimated channel obtained in different iterations can only improve the accuracy of channel estimation under conditions of low signal-to-noise ratio (SNR), whereas it degrades accuracy under conditions of high SNR. To address this issue, an improved weighted matching pursuit algorithm is proposed, which obtains a suitable weight value u_op by training the channel data. The step of the weight value increasing with successive iterations is calculated according to the sparsity of the channel and u_op. Adjusting the weight value adaptively over the iterations can further improve the accuracy of estimation. The results of simulations conducted to evaluate the proposed algorithm show that it exhibits improved performance in terms of accuracy compared to previous methods under conditions of both high and low SNR.

• Journal of Biomedical Engineering Research
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• v.23 no.1
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• pp.61-72
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• 2002

In this parer, a new harmonic imaging technique is Proposed and evaluated experimentally. In the Proposed method. a weighted chirp signal with a hanning window is transmitted. The RF samples obtained on each array element are individually compressed by correlating with the reference signal defined as the 2nd harmonic component($2f_0$) of a transmitted chirp signal generated in a square-law system. The correlator output will then consist of the compressed version of the $2f_0$ component generated in tissue and the crosscorrelation sequence of the fundamental($f_0$) and 2f$_{0}$components. The Proposed method uses the compressed $2f_0$ component to form an image. for which the crosscorrelation term should be suppressed below at least -50dB. The Proposed method has two process, 2f$_{0}$-correlation and $2f_0$-correlation(PI) . $2f_0$-correlation can successfully eliminate the $f_0$ component with a single transmit-receive events and therefore is more efficient than the conventional Pulse inversion method in terms of the frame rate. 2i)-correlation(Pl) Performs pulse compression after applying pulse inversion method for the 2nd harmonic image with high resolution and SNR. Another advantage of the proposed method is that the SNR of 2nd harmonic imaging can be improved without limitation by increasing the duration of the chirp signal. The proposed method was verified through both the computer simulations and actual experiments .ts .

• Journal of electromagnetic engineering and science
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• v.11 no.4
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• pp.250-256
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• 2011

This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.151-154
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• 2001

In this Paper, a new harmonic imaging technique is proposed and evaluated experimentally. In the proposed method, a weighted chin signal with a hanning window is transmitted. The RF samples obtained on each array element are individually compressed by correlating with the reference signal defined as the 2nd harmonic (2f0) component of a transmitted chirp signal generated in a square-law system. The proposed method uses the compressed 2f0 component to form an image, for which the crosscorrelation term with f0 component should be suppressed below at least -60dB. After experiment, the 6dB pulse width and peak sidelobe level of the compressed 2f0 component were 0.7us and -60dB, respectively. This result shows that the proposed method can successfully eliminate the f0 component with a single transmit-receive event and therefore is more efficient than the conventional pulse inversion (PI) method in terms of frame rate. We also observed that the 2nd harmonic compont starts to decrease for source pressure higher than 210kPa in water, which implies that SNR of the 2nd harmonic imaging using short pulses cnanot be incresed beyond a certain limit.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.187-190
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• 2001

A new ultrasound imaging technique based on simultaneous multiple transmit focusing using orthogonal modified Golay codes is presented. modified Golay codes are used to increase signal-to-noise-ratio(SNR) and maximize the transmit power efficiency(TPE). Conventional Golay codes consist of a pair of complementary codes with same length and can be compressed into a delta-like signal due to their complementary property. In the present work, two modified Golay codes focused at different depths are transmitted at the same time, which are mutually orthogonal. On receive, these orthogonal modified Golay codes are separately compressed into two short pulses and individually focused. These two focused beam are combined to form a frame of image with improved lateral resolution. Computer simulations are performed to verity the proposed method improves the lateral resolution of image compared with the conventional echo system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2949-2963
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• 2019

A novel distributed compress-and-forward (CF) system based on multi-relay network is presented. In this system, as the direct link between the source and destination is invalid due to some reasons, such as the limited power, special working environment, or even economic factors, relays are employed to receive analog signals and carry on distributed compressed encoding. Subsequently, the digital signals are transmitted to the destination via wireless channel. Moreover, a theoretical analysis for the system is provided by utilizing the Chief Executive Officer (CEO) theory and Shannon channel capacity theory, and the rate-distortion function as well as the connection between the transmission rate and the channel capacity are constructed. In addition, an optimal signal-to-noise ratio (SNR) -based power allocation method is proposed to maximize the quantization SNR under the limited total power. Simulation result shows that the proposed CF system outperforms the amplify-and-forward (AF) system versus the SNR performance.

• Korean Journal of Digital Imaging in Medicine
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• v.6 no.1
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• pp.31-40
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• 2003

Purpose : In a PACS(Picture Archiving Communications System) environment, which is a very important component in a digital medical environment, the compression of digital medical images is a necessary and effective feature. In a current system where JPEG is applied to the compression of medical images, this study is to examine effectiveness and suitability when the JPEG2000, a more advanced compression algorithm for still images, is applied to the compression of medical images. In this thesis, we attempt to address the compressibility for effective clinical usage when compressing medical images, applying the objectivization of clinical evaluation as a function of compressibility. In the experiment al method, the compression was applied at a fixed rate using JPEG2000, and the n the result was compared with compressed images by JPEG. Method : For the performance evaluation, we choose SNR(Signal to Noise Ratio) measurement of an objective evaluation of definition and analyze a subjective evaluation by the ROC(Receiver Operating Characteristic) method. The results of the experiment showed that in the case of JPEG2000 there is hardly any distortion of images, even at high compression ratio(100:1), while regarding noise, the SNR remains around about 40dB, which is also relatively high. Before reading by reference to evaluative materials concerning objective compressed images, it is impossible to apply high compression to images : however, after reading, this can be applied to images that have already existed for some time.

• MALSORI
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• no.61
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• pp.75-86
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• 2007

In this paper, we propose a scalable audio coder, which has a variable bandwidth from the narrowband speech bandwidth to the audio bandwidth and also has a bit-rate from 8 to 320 kbits/s, in order to cope with the quality of service(QoS) according to the network load. First of all, the proposed scalable coder splits bandwidth of the input audio into narrowband up to around 4 kHz and above. Next, the narrowband signals are compressed by a speech coding method compatible to an existing standard speech coder such as G.729, and the other signals whose bandwidth is above the narrowband are compressed on the basis of a psychoacoustic model. It is shown from the objective quality tests using the signal-to-noise ratio(SNR) and the perceptual evaluation of audio quality(PEAQ) that the proposed scalable audio coder provides a comparable quality to the MPEG-1 Layer III (MP3) audio coder.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.85-88
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• 1999

Adapted Local Trigonometric Transforms은 매우 높은 energy compaction을 가지므로 음성 및 영상신호에 이용하려는 시도가 이루어지고 있다. [1] 그러나 이 경우 복원 된 신호에는 시간 영역에서 불연속점이 발생하여 일종의 tick noise가 발생한다. 또한 phase성분을 잃게 되어 금속성 잡음도 추가하여 나타난다. 본 논문에서는 이러한 문제점을 해결하기 위한 Polynomial fitting 방식과 Wavelet Packet Transforms 방식을 제안한다. Polynomial fitting 방식으로는 시간축상에서 발생하는 문제를 해결하고 Wavelet Packet Transforms으로 Phase 문제를 해결한다. [2,3] 실험결과, 압축이전의 신호와 비교할 때 SNR에 있어서 개선을 보이며 tick noise와 금속성 잡음이 제거된 개선된 신호음을 확인 할 수 있었다.