• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.832-835
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• 1987

This paper proposes a new method of generating binary random sequences using a randomly sampled M-sequence. In this paper two methods of sampling are proposed. Expected values of the autocorrelation function of the sequence generated by these methods are calculated theoretically. From the results of computer simulation, it is shown that using these methods, we can get binary random sequences which have good random properties.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.829-840
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• 2013

This paper proposes a modified RRT (Rapidly exploring Random Tree) algorithm utilizing a heuristic input analysis and suggests a test case generation method from Simulink/Stateflow model using the proposed RRT algorithm. Though the typical RRT algorithm is an efficient method to solve the reachability problem to definitely be resolved for generating test cases of model in a black box manner, it has a drawback, an inefficiency of test case generation that comes from generating random inputs without considering the internal states and the test targets of model. The proposed test case generation method increases efficiency of test case generation by analyzing the test targets to be satisfied at the current state and heuristically deciding the inputs of model based on the analysis during expanding an RRT, while maintaining the merit of RRT algorithm. The proposed method is evaluated with the models of ECUs embedded in a commercial passenger's car. The performance is compared with that of the typical RRT algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.59-64
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• 2024

The small tracking radar randomly changes the transmission period to avoid deceptive signals such as RGPO (Range Gaet Pull Off) operated on the target. Since the code repeats after a specific section, it becomes difficult to avoid a deceptive signal when the repetition is exposed. In this paper, a more realistic transmission pulse code is generated by adding random code generation through FPGA and system white noise. We present the research results of code generation that generates PRF that can avoid repetition while using pseudo-random code in EPROM using FPGA. Also, the result of designing random PRF pulse was confirmed by applying it to tracking radar.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.7
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• pp.526-531
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• 2003

Recently, many BIST(Built-in Self Test) schemes have been researched to reduce test time and hardware. But, most BIST schemes about pattern generation are for deterministic pattern generation. In this paper a new pseudo-random BIST scheme is provided to reduce the existing test hardware and keep a reasonable length of test time. Theoretical study demonstrates the possibility of the reduction of the hardware for pseudo-random test with some explanations and examples. Also the experimental results show that in the proposed test scheme the hardware for the pseudo-random test is much less than in the previous scheme and provide comparison of test time between the proposed scheme and the current one.

• Journal of IKEEE
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• v.24 no.1
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• pp.52-58
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• 2020

This paper describes a hardware implementation of a true random number generator (TRNG) for information security applications. A new approach for TRNG design was proposed by adopting random transition rules in cellular automata and applying different transition rules at every time step. The TRNG circuit was implemented on Spartan-6 FPGA device, and its hardware operation generating random data with 100 MHz clock frequency was verified. For the random data of 2×10⁷ bits extracted from the TRNG circuit implemented in FPGA device, the randomness characteristics of the generated random data was evaluated by the NIST SP 800-22 test suite, and all of the fifteen test items were found to meet the criteria. The TRNG in this paper was implemented with 139 slices of Spartan-6 FPGA device, and it offers 600 Mbps of the true random number generation with 100 MHz clock frequency.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1061-1068
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• 2012

In this paper, The Next Generation High Speed Railway inverter system using Hybrid Random Pulse Width Modulation (Hybrid RPWM) is proposed to reduce electromagnetic noise. To verify the validity of study, simulation results of the Next Generation High Speed Railway Inverter system using the proposed method was compared with the system using conventional method. A simulation program is developed using Matlab/Simulink. The results show that the voltage and current harmonics of the Next Generation High Speed Railway Inverter system using Hybrid RPWM significantly decrease and spread into wide band area.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1623-1635
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• 2011

Fourth-generation (4G) cellular communication systems must provide different quality-of-service (QoS) to users according to the service type, membership class, and usage case of each user. For the purpose of user's QoS differentiation, we propose an enhanced uplink random access scheme for bandwidth request. More specifically, we divide a bandwidth request channel into two parts: One is a primary region and the other is a secondary region. Then, each region has a unique minimum access class that allows only specific users to perform random access through that region. By doing so, we can reduce collision probability and increase the success probability of bandwidth request. From the perspective of standardization, we presented this scheme in the IEEE 802.16m Session #66 held on March 2010. As a result, the concept of the proposed scheme and required messages were defined in the 802.16m standard.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.531-540
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• 2008

An Adaptive Random Testing(ART) is one of test case generation algorithms, which was designed to get better performance in terms of fault-detection capability than that of Random Testing(RT) algorithm by locating test cases in evenly spreaded area. Two ART algorithms, such as Distance-based ART(D-ART) and Restricted Random Testing(RRT), had been indicated that they have significant drawbacks in computations, i.e., consuming quadratic order of runtime. To reduce the amount of computations of D-ART and RRT, iterative partitioning of input domain strategy was proposed. They achieved, to some extent, the moderate computation cost with relatively high performance of fault detection. Those algorithms, however, have yet the patterns of non-uniform distribution in test cases, which obstructs the scalability. In this paper we analyze the distribution of test cases in an iterative partitioning strategy, and propose a new method of input domain enlargement which makes the test cases get much evenly distributed. The simulation results show that the proposed one has about 3 percent of improvement in terms of mean relative F-measure for 2-dimension input domain, and shows 10 percent improvement for 3-dimension space.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.180-191
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• 2008

An Adaptive Random Testing (ART) is one of test case generation algorithms that are designed to detect common failure patterns within input domain. The ART algorithm shows better performance than that of pure Random Testing (RT). Distance-bases ART (D-ART) and Restriction Random Testing (RRT) are well known examples of ART algorithms which are reported to have good performances. But significant drawbacks are observed as quadratic runtime and non-uniform distribution of test case. They are mainly caused by a huge amount of distance computations to generate test case which are distance based method. ART through Iterative Partitioning (IP-ART) significantly reduces the amount of computation of D-ART and RRT with iterative partitioning of input domain. However, non-uniform distribution of test case still exists, which play a role of obstacle to develop a scalable algerian. In this paper we propose a new ART method which mitigates the drawback of IP-ART while achieving improved fault-detection capability. Simulation results show that the proposed one has about 9 percent of improved F-measures with respect to other algorithms.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.19-26
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• 2008

In this paper, we propose a dynamic prediction algorithm to predict the bond price using actual data set of treasure note (T-Note). The proposed algorithm is based on term structure model of the interest rates, which takes place in various financial modelling, such as the standard Gaussian Wiener process. To obtain cumulative distribution functions (CDFs) of actual data for the interest rate measurement used, we use the natural cubic spline (NCS) method, which is generally used as numerical methods for interpolation. Then we also use the random number generation scheme (RNGS) to calculate the pricing of bond through the obtained CDF. In empirical computer simulations, we show that the lower values of precision in the proposed prediction algorithm corresponds to sharper estimates. It is very reasonable on prediction.