• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.3
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• pp.423-426
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• 2015

Current verification methods for on-chip memory have been implemented using coverpoints that are generated based on a single operation. These coverpoints cannot consider the influence of other memory banks in a busy state. In this paper, we propose a method in which the coverpoints account for all operations executed on different memory banks. In addition, a new constrained random vector generation method is proposed to reduce the required random vectors for the multi-operation-based coverpoints. The simulation results on NAND flash memory show 100% coverage with 496,541 constrained random vectors indicating a reduction of 96.4% compared with conventional random vectors.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.65-72
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• 1995

The effects of random errors in array weight and sensor positions on the performance of a Linearly constrained linear sensor array is analyzed in a weight vector space. It is observed that a nonorthogonality exists between an optimum weight vector and the steering vector of an interference direction du e to random errors. A novel approach to improving the nulling performance by compensating for the nonorthogonality is proposed. Computer simulation results are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4A
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• pp.269-277
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• 2012

When there are mismatches between the beamforming steering vector and the array response vector for the desired signal, the performance can be severely degraded as the adaptive array attempts to suppress the desired signal as well as interferences. In this paper, an robust method is proposed for the adaptive array in the presence of both direction errors and random errors in the steering vector. The proposed method first finds a signal-plus-interference subspace (SIS) from the correlation matrix, which in turn is exploited to extract an interference subspace based on the structure of a uniform linear array (ULA), the effect of the desired signal direction vector being reduced as much as possible. Then, the weight vector is attained to be orthogonal to the interference subspace. Simulation shows that the proposed method, in terms of signal-to-interference plus noise ratio (SINR), outperforms existing ones such as the doubly constrained robust Capon beamformer (DCRCB).

• Journal of IKEEE
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• v.18 no.3
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• pp.305-312
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• 2014

IIt takes a lot of time and needs the workloads to verify the RTL code used in complex system like a nuclear control system which is required high level reliability using simple testbench. UVM has a layered testbench architecture and it is easy to modify the testbench to improve the code coverage. A test vector can be easily constructed in the UVM, since a constrained random test vector can be used even though the construction of testbench using UVM. We showed that the UVM testbench is easier than the verilog testbench for the analysis and improvement of code coverage.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.67-72
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• 2012

In this paper a new method of handling linear constraints for the genetic algorithm is suggested. The method is designed to maintain the feasibility of offsprings during the evolution process of the genetic algorithm. In the genetic algorithm, the chromosomes are coded as the vectors in the real vector space constrained by the linear constraints. A method of handling the linear constraints already exists in which all the constraints of equalities are eliminated so that only the constraints of inequalities are considered in the process of the genetic algorithm. In this paper a new method is presented in which all the constraints of inequalities are eliminated so that only the constraints of equalities are considered. Several genetic operators such as arithmetic crossover, simplex crossover, simple crossover and random vector mutation are designed so that the resulting offspring vectors maintain the feasibility subject to the linear constraints in the framework of the new handling method.

• Journal of IKEEE
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• v.28 no.3
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• pp.412-418
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• 2024

This paper proposes an effective method for detecting hacking attacks in automotive CAN bus using the RANSAC (Random Sample Consensus) algorithm. Conventional deep learning-based detection techniques are difficult to be applied to resource-constrained environments such as vehicles. In this paper, the attack detection performance in vehicular CAN communication has been improved by utilizing the lightweight nature and efficiency of the RANSAC algorithm. The RANSAC algorithm can perform effective detection with minimal computational resources, providing a practical hacking detection solution for vehicles.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.2
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• pp.106-114
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• 2010

We proposed an unified design methodology and verification platform for giga-scale System on Chip (SoC). According to the growth of VLSI integration, the existing RTL design methodology has a limitation of a production gap because a design complexity increases. A verification methodology need an evolution to overcome a verification gap. The proposed platform includes a high level synthesis, and we develop a power-aware verification platform for low power design and verification automation using it's results. We developed a verification automation and power-aware verification methodology based on control and data flow graph (CDFG) and an abstract level language and RTL. The verification platform includes self-checking and the coverage driven verification methodology. Especially, the number of the random vector decreases minimum 5.75 times with the constrained random vector algorithm which is developed for the power-aware verification. This platform can verify a low power design with a general logic simulator using a power and power cell modeling method. This unified design and verification platform allow automatically to verify, design and synthesis the giga-scale design from the system level to RTL level in the whole design flow.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1550-1556
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• 1997

In this paper, we apply the evolutionary algorithm to the combinatorial optimization problem. Evolutionary algorithm useful for the optimization of the large space problem. This paper propose a method for the reuse of wastes of light water in atomic reactor system. These wastes contain several reusable elements, and they should be carefully selected and blended to satisfy requirements as an input material to the heavy water atomic reactor system. This problem belongs to an NP-hard like the 0/1 knapsack problem. Two evolutionary strategies are used as approximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method which perform the feasible test and solution evaluation by using the vectored knowledge in problem domain. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.1-9
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• 1997

These papers propose an evolutionary algorithm for re-using output of waste fuel of light water reactor system in nuclear power plants. Evolutionary algorithm is useful for optimization of the large space problem. The wastes contain several re-useable elements, and they should be carefully selected and blended to satisfy requirements as input material to the heavy water nuclear reactor system. This problem belongs to a NP-hard like the 0/1 Knapsack problem. Two evolutionary strategies are used as a, pp.oximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method, which performs the feasible teat and solution evaluation by using the vectorized data in problem. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.