• The Journal of the Acoustical Society of Korea
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• 제20권2호
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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.

• Wind and Structures
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• 제3권1호
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• pp.1-10
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• 2000

Recently, an efficient and practical method has been developed for the generation of univariate non-Gaussian wind pressure time histories on low building roofs; this methodology requires intermittent exponential random numbers for the simulation. On the other hand, the conventional spectral representation scheme with random phase is found suitable for the generation of univariate Gaussian wind pressure time histories on low building roofs; this simulation scheme requires uniform random numbers. The dependency of these simulation methodologies on the random number generator is one of the items affecting the accuracy of the simultion result; therefore, an attempt has been made to investigate the issue. This note presents the observed sensitivity of random number sets in repetitive simulations of Gaussian and non-Gaussian wind pressures.

• ETRI Journal
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• 제32권1호
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• pp.93-101
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• 2010

A true random number generator (TRNG) is widely used to generate secure random numbers for encryption, digital signatures, authentication, and so on in crypto-systems. Since TRNG is vulnerable to environmental changes, a deterministic function is normally used to reduce bias and improve the statistical properties of the TRNG output. In this paper, we propose a linear corrector for secure TRNG. The performance of a linear corrector is bounded by the minimum distance of the corresponding linear error correcting code. However, we show that it is possible to construct a linear corrector overcoming the minimum distance limitation. The proposed linear corrector shows better performance in terms of removing bias in that it can enlarge the acceptable bias range of the raw TRNG output. Moreover, it is possible to efficiently implement this linear corrector using only XOR gates, which must have a suitable hardware size for embedded security systems.

• Journal of the Korean Institute of Telematics and Electronics B
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• 제33B권9호
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• pp.107-116
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• 1996

In the stochastic structure for doing exact calculationk, an input number must be changed to a pulse stream. Because the performance of random number generator (RNG) is controlled by its initial condition, we suggested newly modified cellular automata (MCA) which is uses a counter for boundary condition. We compared newly suggested MCA RNG to previously reported RNGs using the AND gate passing outputs which have the same meaning of multiplication in the stochastic calculation. In order to use stochastic we studied about the method, one large RNG can generate many small random numbers. In this method, RNG must have large drive capabilities for many input comparator. So we studied about drive capabilities using BiCMOS circuit and CMOS circit by SPICE.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제27권3호
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• pp.449-457
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• 2017

In this paper, we analyze the security and performance of the Quantis Quantum random number generator in terms of cryptography through experiments. The Quantis' post-processing is designed to output full-entropy via bit-matrix-vector multiplication based on mathematical background, and we used the min-entropy estimating test of NIST SP 800-90B so as to verify whether the output is full-entropy. Quantis minimizes the effect on the random bit rate by using an optimization technique for bit-matrix-vector multiplication, and compared the performance to conditioning functions of NIST SP 800-90B by measuring the random bit rate. Also, we have distinguished what is in Quantis' post-processing to the standard model of NIST in USA and BSI in Germany, and in case of applying Quantis to cryptographic systems in accordance with the CMVP standard, it is recommended to use the output of Quantis as the seed of the approved DRBG.

• The Transactions of the Korean Institute of Electrical Engineers D
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• 제53권7호
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• pp.525-530
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• 2004

A classifier was constructed by using a generalized regression neural network (GRU) and random generator (RG), which was applied to classify DNA sequences. Three data sets evaluated are eukaryotic and prokaryotic sequences (Data-I), eukaryotic sequences (Data-II), and prokaryotic sequences (Data-III). For each data set, the classifier performance was examined in terms of the total classification sensitivity (TCS), individual classification sensitivity (ICS), total prediction accuracy (TPA), and individual prediction accuracy (IPA). For a given spread, the RG played a role of generating a number of sets of spreads for gaussian functions in the pattern layer Compared to the GRNN, the RG-GRNN significantly improved the TCS by more than 50%, 60%, and 40% for Data-I, Data-II, and Data-III, respectively. The RG-GRNN also demonstrated improved TPA for all data types. In conclusion, the proposed RG-GRNN can effectively be used to classify a large, multivariable promoter sequences.

• Journal of applied mathematics & informatics
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• 제15권1_2호
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• pp.363-375
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• 2004

In this paper, We show that the bandpass random signals of the form ∑$_{\alpha}$$\alpha$$_{\alpha}$ a Sin(2$\pi$f$_{\alpha}$t + b$_{\alpha}$) where a$_{\alpha}$ being a random number in [0,1], f$_{\alpha}$ a random integer in a given frequency band, and b$_{\alpha}$ a random number in [0, 2$\pi$], generate Gaussian white noise signals and hence they are adequate for simulating Continuous Markov processes. We apply the result to the fluctuation-dissipation formula for the Johnson noise and show that the probability distribution for the long term average of the power of the Johnson noise is a X$^2$ distribution and that the relative error of the long term average is (equation omitted) where N is the number of blocks used in the average.error of the long term average is (equation omitted) where N is the number of blocks used in the average.

• Journal of the Korea Society of Computer and Information
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• 제25권11호
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• pp.97-104
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• 2020

In this paper, we propose a random number generator PP(PingPong256) and a shuffle technique to improve the problem that the encrypted image is damaged due to a lot of noise by the channel coding of wireless communication recommended in the special environment of space. The PP can constantly generate random numbers by entering an initial value of 512 bits. Random numbers can be encrypted through images and exclusive logical computations. Random numbers can be encrypted through images and exclusive logical computations. The shuffle technique randomly rearranges the image pixel positions while synchronizing the image pixel position and the random number array position and moving the random number arrangement in ascending order. Therefore, the use of PP and shuffle techniques in channel coding allows all pixels to be finely distributed and transmit high-quality images even in poor transmission environments.

• ETRI Journal
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• 제43권3호
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• pp.571-571
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• 2021

• Journal of the Institute of Electronics Engineers of Korea SD
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• 제46권8호
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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.