Coding Prony’s method in MATLAB and applying it to biomedical signal filtering

BMC Bioinformatics

Table 1 Result of approximation of synthetic functions

Number of functions g_i[n] correctly approximated
N	p	LS	TLS	MPM
1024	30	902	811	990
	40	868	499	1000
	50	826	499	1000
	100	997	322	1000
	150	1000	315	1000
	200	1000	375	1000
	250	1000	358	1000
	300	1000	288	1000
	400	1000	224	1000
	500	999	137	1000
512	30	941	741	1000
	40	974	660	1000
	50	996	682	1000
	60	999	618	1000
	70	1000	544	1000
	100	1000	565	1000
	150	1000	622	1000
	200	1000	579	1000
	220	1000	517	1000
	250	999	516	1000
256	30	984	909	1000
	40	998	872	1000
	50	998	855	1000
	60	1000	826	1000
	70	1000	778	1000
	80	1000	862	1000
	90	1000	827	1000
	100	1000	758	1000
	110	1000	733	1000
	120	996	758	1000
128	20	994	995	994
	30	1000	960	1000
	40	1000	956	1000
	50	1000	931	1000
	60	1000	910	1000
64	20	1000	1000	999
	25	1000	969	1000
	30	1000	970	1000
Average value per method		\( \overline{\mathrm{LS}}=986.08 \)	\( \overline{\mathrm{TLS}}=677.39 \)	\( \overline{\mathrm{MPM}}=999.55 \)

ISSN: 1471-2105