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Sum-α Stopping Criterion for Turbo Decoding

Ouardi Aissa

International Journal of Electronics and Telecommunications

2021

Vol. 67, No. 3

477--482

In this article, we propose a new stopping criterion for turbo codes. This criterion is based on the behaviour of the probabilistic values alpha 'α' calculated in the forward recursion during turbo decoding. We called this criterion Sum-α. The simulation results show that the Bit Error Rates BER are very close to those of the Cross-Entropy CE criterion with the same average number of iterations.

Variance as a Stopping Criterion for Genetic Algorithms with Elitist Model

Bhandari D., Murthy C.A., Pal S.K.

Fundamenta Informaticae

2012

Vol. 120, nr 2

145-164

Genetic Algorithm (GA) has now become one of the leading mechanisms in providing solution to complex optimization problems. Although widely used, there are very few theoretical guidelines for determining when to stop the algorithm. This article establishes theoretically that the variance of the best fitness values obtained in the iterations can be considered as a measure to decide the termination criterion of a GA with elitist model (EGA). The criterion automatically takes into account the inherent characteristics of the objective function. Implementation issues of the proposed stopping criterion are explained. Its difference with some other stopping criteria is also critically analyzed.