• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.251-268
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• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.587-587
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• 2006

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.68-75
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• 1997

Spectral subtraction is widely-used preprocessing technique for speech recognition in additive noise environments, but it requires a good estimate of the noise power spectrum. In this paper, we employ the histogram technique for the estimation of noise spectrum. This technique has advantages over other noise estimation methods in that it does not requires speech/non-speech detection and can estimate slowly-varying noise spectra. According to the speaker-independent isolated word recognition in both colored Gaussian and car noise environments under various SNR conditions. Histogram-technique-based spectral subtraction method yields superier performance to the one with conventional noise estimation method using the spectral average of initial frames during non-speech period.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.245-248
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• 2006

A particle filter is one of the most famous filters. The reason why the particle filter is widely used is that particle deals with the state estimation problem for not only linear models with Gaussian noise but also the non-linear models with non-Gaussian noise and it receives great attention from many engineering fields. In the point of view state estimator, particle filter is feedforward observer. According to the characteristic of dynamic system, the feedforward observer can estimate real state. However, the speed of convergence of feedforward observer between the actual state and the estimated state cannot be satisfied. Since the particle filter is a sort of feedforward observer, the convergence speed of particle filter is slow, and the particle filter cannot estimate actual state like particle collapse problem. In order to overcome the limitation of particle filter as a kind of feedfoward estimator, we propose a new particle filter which has feedback term, called particle filter with feedback. Our proposed method is analyzed theoretically and studied by computer simulation. Comparisons are made with other filtering mehod.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.453-458
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• 2019

In this study we analyzed the tendency of the image characteristic by changing filtering factor for the proposed fast non local means (FNLM) noise reduction algorithm with designed Male Adult mesh (MASH) phantom through Geant4 application for tomographic emission (GATE) simulation program. To accomplish this purpose, MASH phantom for human copy was designed through the GATE simulation program. In addition, we acquired degraded image by adding Gaussian noise with a value of 0.005 using the MATALB program in MASH phantom. Moreover, in degraded image, the FNLM noise reduction algorithm was applied by changing the filtering factors, which set to 0.005, 0.01, 0.05, 0.1, 0.5, and 1.0 value, respectively. To quantitatively evaluate, the coefficient of variation (COV), signal to noise ratio (SNR), and contrast to noise ratio (CNR) were calculated in reconstructed images. Results of the COV, SNR and CNR were most improved in image with a filtering factor of 0.05 value. Especially, the COV was decreased with increasing filtering factor, and showed nearly constant values after 0.05 value of the filtering factor. In addition, SNR and CNR were showed that improvement with increasing filtering factor, and deterioration after 0.05 value of the filtering factor. In conclusion, we demonstrated the significance of setting the filtering factor when applying the FNLM noise reduction algorithm in degraded image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.237-244
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• 2006

I/Q phase unbalance caused by non-ideal circuit components is inevitable physical phenomenons and leads to performance degradation when we implement a practical coherent M-ary phase shift keying(M-PSK) demodulator. In this paper, we present an exact and general expression involving two-dimensional Gaussian Q-functions for the bit error rate(BER) of uniform M-PSK with I/Q phase unbalance over an additive white Gaussian noise(AWGN) channel. First we derive a BER expression for the k-th bit of 8, 16-PSK signal constellations when Gray code bit mapping is employed. Then, from the derived k-th bit BER expression, we present the exact and general average BER expression for M-PSK with I/Q phase unbalance. This result can readily be applied to numerical evaluation for various cases of practical interest in an I/Q unbalanced M-PSK system, because the one- and two-dimensional Gaussian Q-functions can be easily and directly computed using commonly available mathematical software tools.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.10
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• pp.1161-1168
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• 2010

The FHSS(Frequency Hopping Spread Spectrum), in which a transmitter changes its carrier frequency according to a certain hopping pattern, is widely used in the military communication system, since it is highly resistant to deliberate Jamming. However, the difference of BER performance of satellite communication system which using the different modulation scheme and Jamming model was not studied. Thus, in this paper, we consider PBNJ(Partial-Band Noise Jamming) and WPBJ(Worst case Partial-Band noise Jamming) as Jamming models, and evaluate BER(Bit Error Rate) performances of NC-MFSK(Non-Coherent M-ary Frequency-Shift Keying), SDPSK(Symmetric Differential Phase-Shift Keying), and GMSK(Gaussian filtered Minimum-Shift Keying) modulation schemes. Based on the results, we suggest the best transmission method for each condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1920-1925
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• 2012

In this paper, we propose a novel method to improve the performance of the improved minima controlled recursive averaging (IMCRA) in non-stationary noisy environment. The conventional IMCRA algorithm efficiently estimate the noise power by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. Since the minimum of smoothing parameter is defined as 0.85, it is difficult to obtain the robust estimates of the noise power in non-stationary noisy environments that is rapidly changed the spectral characteristics such as babble noise. For this reason, we proposed the modified IMCRA, which adaptively estimate and updata the noise power according to the noise type classified by the Gaussian mixture model (GMM). The performances of the proposed method are evaluated by perceptual evaluation of speech quality (PESQ) and composite measure under various environments and better results compared with the conventional method are obtained.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1886-1898
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• 2015

In today’s era of advanced technological developments, the threats to the authenticity and integrity of digital images, in a nutshell, the threats to the Image Forensics Research communities have also increased proportionately. This happened as even for the ‘non-expert’ forgers, the availability of image processing tools has become a cakewalk. This image forgery poses a great problem for judicial authorities in any context of trade and commerce. Block matching based image cloning detection system is widely researched over the last 2-3 decades but this was discouraged by higher computational complexity and more time requirement at the algorithm level. Thus, for reducing time need, various dimension reduction techniques have been employed. Since a single technique cannot cope up with all the transformations like addition of noise, blurring, intensity variation, etc. we employ multiple techniques to a single image. In this paper, we have used Fuzzy logic approach for decision making and getting a global response of all the techniques, since their individual outputs depend on various parameters. Experimental results have given enthusiastic elicitations as regards various transformations to the digital image. Hence this paper proposes Fuzzy based cloning detection and classification system. Experimental results have shown that our detection system achieves classification accuracy of 94.12%. Detection accuracy (DAR) while in case of 81×81 sized copied portion the maximum accuracy achieved is 99.17% as regards subjection to transformations like Blurring, Intensity Variation and Gaussian Noise Addition.

• ETRI Journal
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• v.43 no.2
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• pp.184-196
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• 2021

The research domain of underwater communication has garnered much interest among researchers exploring underwater activities. The underwater environment differs from the terrestrial setting. Some of the main challenges in underwater communication are limited bandwidth, low data rate, propagation delay, and high bit error rate (BER). As such, this study assessed the underwater acoustic (UWA) aspect and explored the expression of error performance based on t-distribution noise. Filter orthogonal frequency-division multiplexing refers to a new waveform candidate that has been adopted in UWA, along with turbo and polar codes. The empirical outcomes demonstrated that the noise did not adhere to Gaussian distribution, whereas the simulation results revealed that the filter applied in orthogonal frequency-division multiplexing could significantly suppress out-of-band emission. Additionally, the performance of the turbo code was superior to that of the polar code by 2 dB at BER 10-3.