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EURASIP Journal on Advances in Signal Processing
Fig. 2 | EURASIP Journal on Advances in Signal Processing

Fig. 2

From: Optimal measurement budget allocation for Kalman prediction over a finite time horizon by genetic algorithms

Fig. 2

Comparison of the mean and minimum (min) cost for the random trial (RT) method, the genetic algorithm (GA) with shuffle crossover (SC), the GA with replace crossover (RC), the GA with count preserving crossover (CPC) and the regular Kalman predictor (regular cost) with respect to the number of cost function evaluations. For the genetic algorithms, one generation corresponds to 100 cost function evaluations

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