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Distributed Storage Codes with Multiple Replication Degrees Using Relative Difference Families (상대 차족을 이용한 복수 반복 차수 분산 저장 부호)

  • Park, Hosung;Kim, Cheol-Sung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.12
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    • pp.1768-1770
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    • 2016
  • In this paper, we propose a construction method of fractional repetition codes, a class of distributed storage codes, using relative difference families. The proposed codes can support multiple replication degrees for data symbols. It is shown via simulation that the proposed codes store more data than the random fractional repetition codes.

Optimization of Unequal Error Protection Rateless Codes for Multimedia Multicasting

  • Cao, Yu;Blostein, Steven D.;Chan, Wai-Yip
    • Journal of Communications and Networks
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    • v.17 no.3
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    • pp.221-230
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    • 2015
  • Rateless codes have been shown to be able to provide greater flexibility and efficiency than fixed-rate codes for multicast applications. In the following, we optimize rateless codes for unequal error protection (UEP) for multimedia multicasting to a set of heterogeneous users. The proposed designs have the objectives of providing either guaranteed or best-effort quality of service (QoS). A randomly interleaved rateless encoder is proposed whereby users only need to decode symbols up to their own QoS level. The proposed coder is optimized based on measured transmission properties of standardized raptor codes over wireless channels. It is shown that a guaranteed QoS problem formulation can be transformed into a convex optimization problem, yielding a globally optimal solution. Numerical results demonstrate that the proposed optimized random interleaved UEP rateless coder's performance compares favorably with that of other recently proposed UEP rateless codes.

A New Hybrid Genetic Algorithm for Nonlinear Channel Blind Equalization

  • Han, Soowhan;Lee, Imgeun;Han, Changwook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.259-265
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    • 2004
  • In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

A Modified FCM for Nonlinear Blind Channel Equalization using RBF Networks

  • Han, Soo-Whan
    • Journal of information and communication convergence engineering
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    • v.5 no.1
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    • pp.35-41
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    • 2007
  • In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

Spectrum Sensing of Cognitive Radio using Multiple Antennas in WiBro Systems (WiBro 시스템에서 다중 안테나를 이용한 인지 무선 스펙트럼 센싱)

  • Baek, Myung-Kie;Heo, Si-Young;Yang, Jae-Soo;Kim, Jin-Young;Kim, Yun-Hyeon
    • 한국정보통신설비학회:학술대회논문집
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    • 2008.08a
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    • pp.379-383
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    • 2008
  • Cognitive Radio (CR) technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problems. Spectrum sensing is one of the most challenging issues in cognitive radio system. In this paper, we focus on the signal detection of WiBro system band. As most of the modulated signals can be treated as cyclostationary random process, we can detect the signal of the OFDM signals in WiBro system. OFDM symbols using WiBro system have several pilot subcarriers and periodic pilots have cyclostationary characteristic. To improve of the detection performance, we get diversity gain using multiple antennas.

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A Study on Blind Nonlinear Channel Equalization using Modified Fuzzy C-Means (개선된 퍼지 클러스터 알고리즘을 이용한 블라인드 비선형 채널등화에 관한 연구)

  • Park, Sung-Dae;Han, Soo-Whan
    • Journal of Korea Multimedia Society
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    • v.10 no.10
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    • pp.1284-1294
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    • 2007
  • In this paper, a blind nonlinear channel equalization is implemented by using a Modified Fuzzy C-Means (MFCM) algorithm. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

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Performance Improvement on Fuzzy C-Means Algorithm for Nonlinear Blind Channel Equalization (비선형 블라인드 채널등화를 위한 퍼지 클러스터 알고리즘의 성능개선)

  • Park, Seong-Dae;Han, Su-Hwan
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2007.05a
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    • pp.382-388
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    • 2007
  • In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

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Blind Nonlinear Channel Equalization by Performance Improvement on MFCM (MFCM의 성능개선을 통한 블라인드 비선형 채널 등화)

  • Park, Sung-Dae;Woo, Young-Woon;Han, Soo-Whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2158-2165
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    • 2007
  • In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.

Comparison of Stereopsis by Influence Factors in Induced Aniseikonia (유발 부등상시에서 영향인자에 따른 입체시의 비교)

  • Jung, Su A;Kim, Hyun Jung
    • Journal of Korean Ophthalmic Optics Society
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    • v.18 no.4
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    • pp.465-471
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    • 2013
  • Purpose: This study was conducted to research effects of influence factors on stereopsis of induced aniseikonia in emmetropia. Methods: 20 college students (a mean age of $22.50{\pm}2.72$ years, 14 males, 6 females) were selected as subjects and all of them had no ocular disease or systemic disease, the refractive correction of spherical equivalent within ${\pm}0.50$ D, the corrected visual acuity of 1.0 or better and the aniseikonia values less than 1% by AWAYA. Subject's dominant eye was checked by Hole in card method and contact lenses of -7.00 ~ +7.00D were fitted to cause anisometropia in dominant eye or non-dominant eye, respectively. And then aniseikonia was induced with spectacles to correct refractive error by contact lenses. Stereopsis was measured by Random Dot Stereo Acuity Test with LEA symbols$^{(R)}$ (Vision Assessment Corporation$^{TM}$, USA). Results: Stereopsis was remarkably reduced by inducing aniseikonia, with induced aniseikonia in dominant eye, with higher diopter of wearing contact lenses to induce anisometropia, with spectacles lenses correction of minus power after fitting contact lenses with plus power and in case of men. Conclusions: It should be considered to correct anisometropia that aniseikonia could cause reduction of stereopsis.

Practical Approach for Blind Algorithms Using Random-Order Symbol Sequence and Cross-Correntropy (랜덤오더 심볼열과 상호 코렌트로피를 이용한 블라인드 알고리듬의 현실적 접근)

  • Kim, Namyong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.3
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    • pp.149-154
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    • 2014
  • The cross-correntropy concept can be expressed with inner products of two different probability density functions constructed by Gaussian-kernel density estimation methods. Blind algorithms based on the maximization of the cross-correntropy (MCC) and a symbol set of randomly generated N samples yield superior learning performance, but have a huge computational complexity in the update process at the aim of weight adjustment based on the MCC. In this paper, a method of reducing the computational complexity of the MCC algorithm that calculates recursively the gradient of the cross-correntropy is proposed. The proposed method has only O(N) operations per iteration while the conventional MCC algorithms that calculate its gradients by a block processing method has $O(N^2)$. In the simulation results, the proposed method shows the same learning performance while reducing its heavy calculation burden significantly.