rootmusic Frequencies and power of sinusoids using the root MUSIC algorithm w = rootmusic(x,p) [w,pow] = rootmusic(x,p) [f,pow] = rootmusc(...,fs) [w,pow] = rootmusic(...,'corr') x: int|double - vector|matrix Input signal. In case of a matrix, each row of x represents a seperate observation of the signal. If 'corr' flag is specified, then x is the correlation matrix. If w is not specified in the input, it is determined by the algorithm. If x is real valued, then range of w is [0, pi]. Otherwise, the range of w is [0, 2pi) p: int|double - scalar|vector p(1) is the dimension of the signal subspace p(2), if specified, represents a threshold that is multiplied by the smallest estimated eigenvalue of the signal's correlation matrix. w: int|double - vector w is the vector of normalized frequencies over which the pseuspectrogram is to be computed. pow: the estimated absolute value squared amplitudes of the sinusoids at the frequencies w. fs: int|double - scalar (Default = 1) Sampling rate. Used to convert the normalized frequencies (w) to actual values (f) and vice-versa. corr: If specified, x is interpreted as a correlation matrix rather than a matrix of the signal data. For x to be a correlation matrix, x must be a square matrix and all its eigenvalues must be nonnegative. W = rootmusic(X,P) returns the frequencies in radians/sample for the P complex exponentials (sinusoids) that make up the signal X. The input X is specified either as: A row or column vector representing one observation of the signal A rectangular array for which each row of x represents a separate observation of the signal (for example, each row is one output of an array of sensors, as in array processing), such that x'*x is an estimate of the correlation matrix | peig | pmusic | rooteig References Monson H. Hayes, Statistical Digital Signal Processing And Modeling, & Sons, Inc, [Section 8.6.3] arguments - double - vector frequencies of the complex sinusoids - double - vector absolute value squared amplitudes of the sinusoids at frequencies w