EURASIP Journal on Advances in Signal Processing

Table 3 Root mean square error of Example 3

From: Family of state space least mean power of two-based algorithms

		Root mean square error (dB)
		Example 3
		KF	SSLMS	SSLMF	SSLMSi	SSLME
State x ₁	Gaussian	−14.9484	−13.9622	−14.1395	−14.6637	−14.6965
	Uniform	−14.9438	−13.9619	−14.1506	−14.6729	−14.7018
	Laplace	−14.9330	−13.9600	−14.1397	−14.6654	−14.6985
State x ₂	Gaussian	−14.2212	−13.1412	−13.7200	−14.3676	−14.3167
	Uniform	−14.2242	−13.1367	−13.7295	−14.3708	−14.4115
	Laplace	−14.2198	−13.1355	−13.7170	−14.3652	−14.3153
State x ₃	Gaussian	−8.4244	−7.2323	−7.9750	−8.7182	−8.8679
	Uniform	−8.4201	−7.2197	−7.9772	−8.7156	−8.7881
	Laplace	−8.4095	−7.2197	−7.9665	−8.7122	−8.8612
State x ₄	Gaussian	−7.8682	−6.8915	−7.1522	−7.8059	−8.1534
	Uniform	−7.8713	−6.8930	−7.1616	−7.8149	−7.9130
	Laplace	−7.8669	−6.8911	−7.1511	−7.8057	−8.1535
State x ₅	Gaussian	−11.1405	−9.9399	−10.2366	−10.7061	−8.1534
	Uniform	−11.1391	−9.9325	−10.2373	−10.7057	−7.9130
	Laplace	−11.1303	−9.9349	−10.2329	−10.7033	−8.1535
Observation y ₁	Gaussian	−26.9886	−4.7978	−5.0163	−5.4818	−5.6242
	Uniform	−26.9860	−4.7960	−5.0221	−5.4861	−5.5343
	Laplace	−26.9872	−4.7963	−5.0150	−5.4816	−5.6243
Observation y ₂	Gaussian	−23.66444	−7.9033	−8.5351	−9.0782	−8.9918
	Uniform	−23.6616	−7.8941	−8.54861	−9.0833	−9.0834
	Laplace	−23.6558	−7.8925	−8.5351	−9.0773	−8.9919

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