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The combining methods may give better performance of IDS systems, and make the detection more effective.
Thomas and Balakrishnan [43] addressed the problem of optimizing the performance of IDS using fusion of multiple sensors.
Joo et al. [36] proposed a NN model to improve the performance of IDS using the asymmetric cost of false positive and false negative errors.
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For example, the BER performance of ID and SD is worse than that of ID-FSD.
The effects of the coefficient of restitution, e, mass ratio, μ, and clearance, d, on the performance of ID are investigated.
Figures 8 and 9 illustrate that BER performance of ID is almost same as that of IC.
However, the computational complexity of IC is much lower than that of ID. Figure 10 shows the BER performance of ID-FSD and IIC schemes with α=6/8, 6 useful subcarriers and α=15/16, 15 useful subcarriers in SEFDM system.
In the simulation of IIC, the number of iteration is 100 in ID, and 1 in IC and in ID-FSD the number of iteration is 10 in ID. Figure 11 shows that when α=14/16 and 14 subcarriers are useful in SEFDM system, the BER performance of ID-FSD is better than that of IIC.
In this simulation, the number of iteration is 50 in ID, and 1 in IC when α=6/8 and the number of iteration is 10 in ID, 1 in IC when α=15/16. Figure 10 shows that when α=6/8 and six subcarriers are useful in SEFDM system, the BER performance of ID-FSD is better than that of IIC.
Since the symbol mapper is a basic constituent part of BICM-ID, the optimization of symbol mappings is crucial for the error performance of BICM-ID.
As mentioned, symbol mapping is crucial for the error performance of BICM-ID.
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CEO of Professional Science Editing for Scientists @ prosciediting.com