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rooteig

Frequency and power content using eigenvector method

Syntax

Description

[w,pow] = rooteig(x,p) estimates the frequency content in the time samples of a signal x, and returns w, a vector of frequencies in rad/sample, and the corresponding signal power in the vector pow in units of power, such as volts^2. The input signal x is specified either as:

You can specify the second input argument p as either:

The extra threshold parameter in the second entry in p provides you more flexibility and control in assigning the noise and signal subspaces.

The length of the vector w is the computed dimension of the signal subspace. For real-valued input data x, the length of the corresponding power vector pow is given by

For complex-valued input data x, pow and w have the same length.

[f,pow] = rooteig(...,fs) returns the vector of frequencies f calculated in Hz. You supply the sampling frequency fs in Hz. If you specify fs with the empty vector [], the sampling frequency defaults to 1 Hz.

[w,pow] = rooteig(...,'corr') forces the input argument x to be interpreted as a correlation matrix rather than a matrix of signal data. For this syntax, you must supply a square matrix for x, and all of its eigenvalues must be nonnegative.

Examples

Find the frequency content in a signal composed of three complex exponentials in noise. Use the modified covariance method to estimate the correlation matrix used by the eigenvector method:

Algorithm

The eigenvector method used by rooteig is the same as that used by peig. The algorithm performs eigenspace analysis of the signal's correlation matrix in order to estimate the signal's frequency content.

The difference between peig and rooteig is:

rooteig is most useful for frequency estimation of signals made up of a sum of sinusoids embedded in additive white Gaussian noise.

See Also

corrmtx, peig, pmusic, powerest method of spectrum, rootmusic, spectrum.eigenvector


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