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:
 [1] Zetterberg L.H. (1969) Estimation of parameter for linear difference equation with application to EEG analysis. Math. Biosci., 5, 227-275. 
 [2] Isaksson A. and Wennberg, A. (1975) Visual evaluation and computer analysis of the EEG - A comparison. Electroenceph. clin. Neurophysiol., 38: 79-86.
 [3] G. Florian and G. Pfurtscheller (1994) Autoregressive model based spectral analysis with application to EEG. IIG - Report Series, University of Technolgy Graz, Austria.

Package: tsa