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Fig. 4 | EURASIP Journal on Advances in Signal Processing

Fig. 4

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

Fig. 4

Histogram of the benefit \(\mathcal {B}= \text {MSE}(\mathcal {M}_{\text {REG}}) - \text {MSE}(\mathcal {M}_{\text {GA}})\) computed over 100,000 realizations for system (31) and (32) with T=100 time steps and N=5 measurements. The histogram approximates the probability density function of the benefit. The red vertical line indicates a null benefit. The mean and standard deviation of the benefit are 0.12Ā±0.38 and the benefit is positive in 64% of the realizations

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