AR_SPA decomposes an AR-spectrum into its compontents [w,A,B,R,P,F,ip] = ar_spa(AR,fs,E); INPUT: AR autoregressive parameters fs sampling rate, provide w and B in [Hz], if not given the result is in radians E noise level (mean square), gives A and F in units of E, if not given as relative amplitude OUTPUT w center frequency A Amplitude B bandwidth - less important output parameters - R residual P poles ip number of complex conjugate poles real(F) power, absolute values are obtained by multiplying with noise variance E(p+1) imag(F) assymetry, - ' - All input and output parameters are organized in rows, one row corresponds to the parameters of one channel see also ACOVF ACORF DURLEV IDURLEV PARCOR YUWA REFERENCES:  Zetterberg L.H. (1969) Estimation of parameter for linear difference equation with application to EEG analysis. Math. Biosci., 5, 227-275.  Isaksson A. and Wennberg, A. (1975) Visual evaluation and computer analysis of the EEG - A comparison. Electroenceph. clin. Neurophysiol., 38: 79-86.  G. Florian and G. Pfurtscheller (1994) Autoregressive model based spectral analysis with application to EEG. IIG - Report Series, University of Technolgy Graz, Austria.