• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.182-188
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• 2001

In this paper, We proposed a pseudo-random bit sequence generator based on the concept of n-dimensional cellular automata which is a method of analyzing dynamical systems. The proposed generator is designed for using and disusing key. And the key size is variable from 128 bits to 256 bits. The generator was estimated to generate 380Mbits/sec under Pentium MMX 200MHz (64M RAM, Windows 98).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1400-1405
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• 2001

In this study, an analysis program to assess the susceptibility of steam generator tubes due to the flow-induced vibration was developed. Analysis of fluid-elastic instability and random turbulence excitation for the U-tube bundle in CE-type steam generator was accomplished. The effective mass distribution along the U-tube was obtained to calculate the natural frequency and dynamic mode shape. Finally, stability ratios and rms vibration amplitude for selected tubes are obtained.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2008.11a
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• pp.147-147
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• 2008

역전파 신경망은 반도체 공정 모델링에 효과적으로 응용되고 있으며, 모델의 예측정확도를 향상시키기 위하여 Random Generator를 개발하였다. Random Generator의 효과가 기존의 모델에 비해 예측정확도의 향상에 영향을 주었음을 알 수 있었다. 모델링에 이용한 실험데이터는 다중 유도결합형 플라즈마 장비를 이용하여 수집하였다.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2007.11a
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• pp.43-44
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• 2007

역전파 신경망은 반도체 공정 모델링에 효과적으로 응용되고 있으며, 모델의 예측정확도를 향상시키기 위하여 Random Generator를 개발하였다. Random Generator의 효과가 기존의 모델에 비해 예측정확도의 향상에 영향을 주었음을 알 수 있었다. 모델링에 이용한 실험데이터는 다중 유도결합형 플라즈마 장비를 이용하여 수집하였다.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2007.04a
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• pp.45-46
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• 2007

역전파 신경망은 반도체 공정 모델링에 효과적으로 응용되고 있으며, 모델의 예측정확도를 향상시키기 위하여 Random Generator를 개발하였다. Random Generator의 효과가 기존이 모델에 비해 예측정확도의 향상에 영향을 주었음을 알 수 있었다. 모델링에 이용한 실험데이터는 다중 유도결합형 플라즈마 장비를 이용하여 수집하였다.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.593-610
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• 2015

Adaptive Rejection Sampling (ARS) method is a well-known random number generator to acquire a random sample from a probability distribution, and has the advantage of improving the proposal distribution during the sampling procedures, which update it closer to the target distribution. However, the use of ARS is limited since it can be used only for the target distribution in the form of the log-concave function, and thus various methods have been proposed to overcome such a limitation of ARS. In this paper, we attempt to compare five random number generators based on ARS in terms of adequacy and efficiency. Based on empirical analysis using simulations, we discuss their results and make a comparison of five ARS-based methods.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.281-288
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• 2005

It is generally accepted that self-similar (or fractal) Processes may provide better models for teletraffic in modem computer networks than Poisson processes. f this is not taken into account, it can lead to inaccurate conclusions about performance of computer networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A generator of pseudo-random self similar sequences, based on the SRA (successive random addition) method, is implemented and analysed in this paper. Properties of this generator were experimentally studied in the sense of its statistical accuracy and the time required to produce sequences of a given (long) length. This generator shows acceptable level of accuracy of the output data (in the sense of relative accuracy of the Hurst parameter) and is fast. The theoretical algorithmic complexity is O(n).

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.3-9
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• 2001

In this paper, a random number generator for simulation of speech-waveform coders was designed. A random number generator having a desired probability density function and a desired power spectral density is discussed and experimental results are presented. The technique is based on Sondhi algorithm which consists of a linear filter and a memoryless nonlinearity. Several methods of obtaining memoryless nonlinearities for some typical continuous distributions are discussed. Sondhi algorithm is analyzed in the time domain using the diagonal expansion of the bivariate Gaussian probability density function. It is shown that the Sondhi algorithm gives satisfactory results when the memoryless nonlinearity is given in an antisymmetric form as in uniform, Cauchy, binary and gamma distribution. It is shown that the Sondhi algorithm does not perform well when the corresponding memoryless nonlinearity cannot be obtained analytically as in Student-t and F distributions, and when the memoryless nonlinearity can not be expressed in an antisymmetric form as in chi-squared and lognormal distributions.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.209-214
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• 2009

The employment of the induction generator is preferable in the natural energy utilization by the minimum maintenance and the mechanical robustness, Another merit is also expected when it is connected to the power network system, because constant-voltage and constant frequency (CVCF) power generation is easily realized in spite of the variation of the rotor speed. However the induction generator needs much amount of the reactive power that reduces power factor in the primary side. The improvement of power factor in the primary side requires large VAR compensator, this point is solved, the merit of the induction machine as a main generator will become more established. This paper proposes a novel approach where the secondary is controlled by a PWM inverter not only to get CVCF power but also to improve the primary power factor. Basically the inverter is controlled so that the field current is supplied from the secondary side in this approach. The required capacity of the inverter is small, because only the slip power is controlled in the secondary side. In the experimental system where the sea wave torque simulator is used, the power factor is well improved by the microcomputer controlled PWM inverter.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.95-101
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• 2009

Random numbers are used in many sorts of applications. Some applications, like simple software simulation tests, communication protocol verifications, cryptography verification and so forth, need various levels of randomness with various process speeds. In this paper, we propose a fast pseudorandom generator module for embedded systems. The generator module is implemented in hardware which can run in two modes, one of which can generate random numbers with higher randomness but which requires six cycles, the other providing its result within one cycle but with less randomness. An ASIP (Application Specific Instruction set Processor) was designed to implement the proposed pseudorandom generator instruction sets. We designed a processor based on the MIPS architecture,, by using LISA, and have run statistical tests passing the sequence of the Diehard test suite. The HDL models of the processor were generated using CoWare's Processor Designer and synthesized into the Dong-bu 0.18um CMOS cell library using the Synopsys Design Compiler. With the proposed pseudorandom generator module, random number generation performance was 239% faster than software model, but the area increased only 2.0% of the proposed ASIP.