Theory of bionic optimization and its application to evolutionary synthesis of digital devices

Rodzin, Sergey; Rodzina, Lada

doi:10.1109/ewdts.2014.7027058

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…Widespread use of the signature register (SR) for testing VLSI is explained by minor hardware costs for their implementation and high detecting ability of SR [8][9][10][11]. The functional principle of signature analysis is extremely simple: in the shift register with a feedback is input data sequence of arbitrary length, which establishes a register in a certain state called signature.…”

Section: Signature Model Of Embedded Self-testmentioning

confidence: 99%

Design of test generator for embedded self-testing

Rodzin

2015

2015 IEEE East-West Design &Amp; Test Symposium (EWDTS)

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The authors consider the built-in self-test signature model. This article describes the analysis shows the ability of signature schemes, as well as the synthesis of the test generator. The approach is generalized for the case when for the synthesis of the test we use several registers with a common synchronization. Experiments have shown that the method of signature generation circuit design allows the test to predict the length of the test when the built-in self-test. In the study, the authors have achieved a substantial reduction in the length of the test sequence, on average by about 80% compared with a test sequence disordered.

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Section: Signature Model Of Embedded Self-testmentioning

confidence: 99%

Design of test generator for embedded self-testing

Rodzin

2015

2015 IEEE East-West Design &Amp; Test Symposium (EWDTS)

Self Cite

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“…С обширным перечнем известных результатов и их обсуждением можно ознакомиться в обзорах [54,55]. Среди российских ученых стоит отметить В. Редько [56,57], Е. Семенкина [58,59], С. Родзина [60,61], А. Еремеева [62][63][64][65].…”

Section: Introductionunclassified

The “One-Fifth Rule” with Rollbacks for Self-Adjustment of the Population Size in the (1 + (λ, λ)) Genetic Algorithm

Bassin

Buzdalov

Shalyto

2021

Aut. Control Comp. Sci.

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Self-adjustment of parameters can signi cantly improve the performance of evolutionary algorithms. A notable example is the (1 + ( , )) genetic algorithm, where adaptation of the population size helps to achieve the linear running time on the OneMax problem. However, on problems which interfere with the assumptions behind the self-adjustment procedure, its usage can lead to the performance degradation. In particular, this is the case with the "one-h rule" on problems with weak tness-distance correlation. We propose a modi cation of the "one-h rule" in order to have less negative impact on the performance in the cases where the original rule is destructive. Our modi cation, while still yielding a provable linear runtime on OneMax, shows be er results on linear function with random weights, as well as on random satis able MAX-3SAT problems.

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Section: Introductionunclassified

The “One-fifth Rule” with Rollbacks for Self-Adjustment of the Population Size in the (1 + (λ,λ)) Genetic Algorithm

Басин

Буздалов

Шалыто

2020

Model. anal. inf. sist.

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Self-adjustment of parameters can significantly improve the performance of evolutionary algorithms. A notable example is the (1 + (λ,λ)) genetic algorithm, where adaptation of the population size helps to achieve the linear running time on the OneMax problem. However, on problems which interfere with the assumptions behind the self-adjustment procedure, its usage can lead to the performance degradation. In particular, this is the case with the “one-fifth rule” on problems with weak fitness-distance correlation.We propose a modification of the “one-fifth rule” in order to have less negative impact on the performance in the cases where the original rule is destructive. Our modification, while still yielding a provable linear runtime on OneMax, shows better results on linear function with random weights, as well as on random satisfiable MAX-3SAT problems.

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Theory of bionic optimization and its application to evolutionary synthesis of digital devices

Cited by 7 publications

References 14 publications

Design of test generator for embedded self-testing

Design of test generator for embedded self-testing

The “One-Fifth Rule” with Rollbacks for Self-Adjustment of the Population Size in the (1 + (λ, λ)) Genetic Algorithm

The “One-fifth Rule” with Rollbacks for Self-Adjustment of the Population Size in the (1 + (λ,λ)) Genetic Algorithm

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