EURASIP Journal on Advances in Signal Processing

Table 1 Root mean square error of example 1

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

		Root mean square error (dB)
		Example 1
		KF	SSLMS	SSLMF	SSLMSi	SSLME
State x ₁	Gaussian	−17.3726	−16.4997	−16.4695	−16.7676	−16.9518
	Uniform	−17.1419	−16.4963	−16.4671	−16.7656	−16.9406
	Laplace	−17.6115	−16.4901	−16.5112	−16.8499	−17.0366
State x ₂	Gaussian	−17.0558	−16.4167	−16.3911	−16.6666	−16.8323
	Uniform	−16.8535	−16.4157	−16.3910	−16.6672	−16.8250
	Laplace	−17.2894	−16.4092	−16.4314	−16.7432	−16.9055
State x ₃	Gaussian	−17.3597	−16.3199	−16.2747	−16.5047	−16.6701
	Uniform	−17.1301	−16.3164	−16.2717	−16.5023	−16.6601
	Laplace	−17.5963	−16.3101	−16.2960	−16.5595	−16.7142
State x ₄	Gaussian	−14.0092	−15.5096	−15.4791	−15.6395	−15.7546
	Uniform	−13.8130	−15.5070	−15.4768	−15.6376	−15.7471
	Laplace	−14.2523	−15.5024	−15.4936	−15.6762	−15.7891
Observation y	Gaussian	−30.4409	−24.3831	−25.3871	−22.6547	−20.8293
	Uniform	−30.4612	−24.3844	−25.3869	−22.6497	−20.9188
	Laplace	−30.4614	−24.3817	−24.8789	−21.9582	−19.3682

Back to article page