Table 3.

Average classification accuracy of different models under the mismatched-condition.

SNR	MLP	CNN	RNN	LSTM	SOM-SNN
Clean	99.45 ± 0.35%	99.85 ± 0.23%	95.35 ± 1.06%	98.40 ± 0.86%	99.60 ± 0.15%
20 dB	55.05 ± 4.30%	61.5 ± 4.71%	25.15 ± 8.86%	47.20 ± 5.36%	79.15 ± 3.70%
10 dB	32.10 ± 8.38%	42.70 ± 5.84%	11.85 ± 2.06%	34.50 ± 10.61%	36.25 ± 1.25%
0 dB	24.60 ± 4.94%	28.40 ± 6.60%	10.10 ± 1.64%	22.35 ± 6.63%	26.50 ± 1.29%
-5 dB	18.40 ± 4.58%	22.65 ± 5.08%	9.20 ± 1.98%	16.60 ± 7.00%	19.55 ± 0.16%
Average	45.92%	51.02%	30.33%	43.81%	52.21%

Experiments are conducted over 10 runs with random weight initialization.

The bold values indicate the best classification accuracies under different SNR.