• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.9
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• pp.73-84
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• 2004

This paper suggests a new scalar multiplication algerian to resist SPA which threatens the security of cryptographic primitive on the hardware recently, and discusses how to apply this algerian Our algorithm is better than other SPA countermeasure algorithms aspect to computational efficiency. Since known SPA countermeasure algorithms have dependency of computation. these are difficult to construct parallel architecture efficiently. To solve this problem our algorithm removes dependency and computes a multiplication and a squaring during inversion with parallel architecture in order to minimize loss of performance. We implement hardware logic with VHDL(VHSIC Hardware Description Language) to verify performance. Synthesis tool is Synplify Pro 7.0 and target chip is Xillinx VirtexE XCV2000EFGl156. Total equivalent gate is 60,508 and maximum frequency is 30Mhz. Our scalar multiplier can be applied to digital signature, encryption and decryption, key exchange, etc. It is applied to a embedded-micom it protects SPA and provides efficient computation.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.822-832
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• 2001

We have implemented an inductive learning system that learns PROSPECTOR-rule-style classification rules from sets of examples. In our a approach, a genetic algorithm is used in which a population consists of rule-sets and rule-sets generate offspring through the exchange of rules relying on genetic operators such as crossover, mutation, and inversion operators. In this paper, we describe our learning environment centering on the syntactic structure and meaning of classification rules, the structure of a population, and the implementation of genetic operators. We also present a method to evaluate the performance of rules and a heuristic approach to generate rules, which are developed to implement mutation operators more efficiently. Moreover, a method to construct a classification system using multiple learned rule-sets to enhance the performance of a classification system is also explained. The performance of our learning system is compared with other learning algorithms, such as neural networks and decision tree algorithms, using various data sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.78-85
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• 2007

With the advancement of the digital broadcasting and popularity of the Internet, recently, many studies are making on the digital watermarking for the copyright protection of digital data. This paper proposes the minimum modification method of motion vector to minimize the degradation of video quality, hiding subtitles of many language and information of OST(original sound track), character profiles, etc. as well as the copyright protection. Our proposed algorithm extracts feature vector by comparing motion vector data with watermark data, and minimize the modification of motion vectors by deciding the inversion of bit. Thus the degradation of video quality is minimized comparing to conventional algorithms. This algorithm also can check data integrity, and retrieve embedded hidden data simply and blindly. And our proposed scheme can be useful for conventional MPEG-1, -2 standards without any increment of bit rate in the compressed video domain. The experimental result shows that the proposed scheme obtains better video quality than other previous algorithms by about $0.5{\sim}1.5dB$.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.606-609
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• 2008

Deconvolution is one of the most used techniques for processing seismic reflection data. It is applied to improve temporal resolution by wavelet shaping and removal of short period reverberations. Several deconvolution algorithms such as predicted, spike, minimum entropy deconvolution and so on has been proposed to obtain such above purposes. Among of them, $\iota_1$ norm proposed by Taylor et al., (1979) and used to compared to minimum entropy deconvolution by Sacchi et al., (1994) has given some advantages on time computing and high efficiency. Theoritically, the deconvolution can be considered as inversion technique to invert the single seismic trace to the reflectivity, but it has not been successfully adopted due to noisy signals of the real data set and unknown source wavelet. After stacking, the seismic traces are moved to zero offset, thus each seismic traces now can be a single trace that is created by convolving the seismic source wavelet and reflectivity. In this paper, the fundamental of $\iota_1$ norm deconvolution method will be introduced. The method will be tested by synthetic data and applied to improve the stacked section of gas hydrate.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.311-319
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• 2001

Statistical reconstruction methods in the context of a Bayesian framework have played an important role in emission tomography since they allow to incorporate a priori information into the reconstruction algorithm. Given the ill-posed nature of tomographic inversion and the poor quality of projection data, the Bayesian approach uses regularizers to stabilize solutions by incorporating suitable prior models. In this work we show that, while the quantitative performance of the standard filtered backprojection (FBP) algorithm is not as good as that of Bayesian methods, the application of spline-regularized smoothing to the sinogram space can make the FBP algorithm improve its performance by inheriting the advantages of using the spline priors in Bayesian methods. We first show how to implement the spline-regularized smoothing filter by deriving mathematical relationship between the regularization and the lowpass filtering. We then compare quantitative performance of our new FBP algorithms using the quantitation of bias/variance and the total squared error (TSE) measured over noise trials. Our numerical results show that the second-order spline filter applied to FBP yields the best results in terms of TSE among the three different spline orders considered in our experiments.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.370-382
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• 2013

Distributed massive MIMO systems, which have high bandwidth efficiency and can accommodate a tremendous amount of traffic using algorithms such as zero-forcing beam forming (ZFBF), may be deployed in large public venues with the antennas mounted under-floor. In this case the channel gain matrix H can be modeled as a multi-banded matrix, in which off-diagonal entries decay both exponentially due to heavy human penetration loss and polynomially due to free space propagation loss. To enable practical implementation of such systems, we present a multi-banded matrix inversion algorithm that substantially reduces the complexity of ZFBF by keeping the most significant entries in H and the precoding matrix W. We introduce a parameter p to control the sparsity of H and W and thus achieve the tradeoff between the computational complexity and the system throughput. The proposed algorithm includes dense and sparse precoding versions, providing quadratic and linear complexity, respectively, relative to the number of antennas. We present analysis and numerical evaluations to show that the signal-to-interference ratio (SIR) increases linearly with p in dense precoding. In sparse precoding, we demonstrate the necessity of using directional antennas by both analysis and simulations. When the directional antenna gain increases, the resulting SIR increment in sparse precoding increases linearly with p, while the SIR of dense precoding is much less sensitive to changes in p.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.527-532
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• 2021

In this paper, we propose an efficient finite field computation method for Rainbow algorithm, which is the only multivariate quadratic-equation based digital signature among the current US NIST PQC standardization Final List algorithms. Recently, Chou et al. proposed a new efficient implementation method for Rainbow on the Cortex-M4 environment. This paper proposes a new multiplication method over the finite field that can reduce the number of XOR operations by more than 13.7% compared to the Chou et al. method. In addition, a multiplicative inversion over that can be performed by a 4x4 matrix inverse instead of the table lookup method is presented. In addition, the performance is measured by porting the software to which the new method was applied onto RaspberryPI 3B+.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4567-4583
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• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.324-329
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• 2003

The public-key cryptosystems such as Diffie-Hellman Key Distribution and Elliptical Curve Cryptosystems are built on the basis of the operations defined in GF(2$^{m}$ ):addition, subtraction, multiplication and multiplicative inversion. It is important that these operations should be computed at high speed in order to implement these cryptosystems efficiently. Among those operations, as being the most time-consuming, multiplicative inversion has become the object of lots of investigation Formant's theorem says $\beta$$^{-1}$ =$\beta$$^{2}$sup m/-2/, where $\beta$$^{-1}$ is the multiplicative inverse of $\beta$$\in$GF(2$^{m}$ ). Therefore, to compute the multiplicative inverse of arbitrary elements of GF(2$^{m}$ ), it is most important to reduce the number of times of multiplication by decomposing 2$^{m}$ -2 efficiently. Among many algorithms relevant to the subject, the algorithm proposed by Itoh and Tsujii[2] has reduced the required number of times of multiplication to O(log m) by using normal basis. Furthermore, a few papers have presented algorithms improving the Itoh and Tsujii's. However they have some demerits such as complicated decomposition processes[3,5]. In this paper, in the case of 2$^{m}$ -2, which is mainly used in practical applications, an efficient algorithm is proposed for computing the multiplicative inverse at high speed by using both the factorization formula x$^3$-y$^3$=(x-y)(x$^2$＋xy＋y$^2$) and normal basis. The number of times of multiplication of the algorithm is smaller than that of the algorithm proposed by Itoh and Tsujii. Also the algorithm decomposes 2$^{m}$ -2 more simply than other proposed algorithms.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.18-25
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• 2005

We derive refraction statics for seismic data recorded in a hard rock terrain, in which there are large and rapid variations in the depth of weathering. The statics corrections range from less than 10 ms to more than 70 ms, often over distances as short as 12 receiver intervals. This study is another demonstration of the importance in obtaining accurate initial refraction models of the weathering in hard rock terrains in which automatic residual statics may fail. We show that the statics values computed with a simple model of the weathering using the Generalized Reciprocal Method (GRM) and the Refraction Convolution Section (RCS) are comparable in accuracy to those computed with a more complex model of the weathering, using least-mean-squares inversion with the conjugate gradient algorithm (Taner et al., 1998). The differences in statics values between the GRM model and that of Taner et al. (1998) systematically vary from an average of 2ms to 4ms over a distance of 8.8 km. The differences between these two refraction models and the final statics model, which includes the automatic residual values, are generally less than 5 ms. The residuals for the GRM model are frequently less than those for the model of Taner et al. (1998). The RCS statics are picked approximately 10 ms later, but their relative accuracy is comparable to that of the GRM statics. The residual statics values show a general correlation with the refraction statics values, and they can be reduced in magnitude by using a lower average seismic velocity in the weathering. These results suggest that inaccurate average seismic velocities in the weathered layer may often be a source of short-wavelength statics, rather than any shortcomings with the inversion algorithms in determining averaged delay times from the traveltimes.