The spectral concentration problem in Fourier analysis refers to finding a time sequence of a given length whose discrete Fourier transform is maximally localized on a given frequency interval, as measured by the spectral concentration.

Spectral concentration

The discrete Fourier transform (DFT) U(f is defined as

In the following, the sampling interval will be taken as Δt = 1, and hence the frequency interval as f ∈ [-,]. U(f) is a periodic function with a period 1.

For a given frequency W such that 0<W< of U(f) on the interval [-W,W] is defined as the ratio of power of U(f) contained in the frequency band [-W,W] to the power of U(f) contained in the entire frequency band [-,]. That is,

It can be shown that U(f for which the DTFT can be confined to a band [-W,W] and made to vanish outside this band.

Statement of the problem

Among all sequences for a given T and W, is there a sequence for which the spectral concentration is maximum? In other words, is there a sequence for which the sidelobe energy outside a frequency band [-W,W] is minimum?

. Thus maximising the power

subject to the constraint that the total power is fixed, say

:

This is an eigenvalue equation for a symmetric matrix given by

It can be shown that this matrix is positive-definite. This sequence is called a 0th–order Slepian sequence (also known as a discrete prolate spheroidal sequence, or DPSS), which is a unique taper with maximally suppressed sidelobes.

It turns out that the number of dominant eigenvalues of the matrix M that are close to 1, corresponds to N=2WT called the Shannon number is called nth–order Slepian sequence (DPSS) (0≤n≤N-1). This nth–order taper also offers the best sidelobe suppression and is pairwise orthogonal. These lower order Slepian sequences form the basis for spectral estimation by multitaper method.

Not limited to time series, the spectral concentration problem can be reformulated to apply in multiple Cartesian dimensions and on the surface of the sphere by using spherical harmonics, for applications in geophysics and cosmology among others.

See also

• Multitaper

• Fourier transform

• Discrete Fourier transform

References

• Partha Mitra and Hemant Bokil. Observed Brain Dynamics, Oxford University Press, USA (2007), Link for book

• Donald. B. Percival and Andrew. T. Walden. Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques, Cambridge University Press, UK (2002).