In applied mathematics, fbsp wavelets are frequency B-spline wavelets. These frequency B-spline wavelets are complex wavelets whose spectrum are spline.
fbsp ( m − f b − f c ) ( t ) := f b sinc m ( t f b m ) e j 2 π f c t {\displaystyle \operatorname {fbsp} ^{(m-\mathrm {fb} -f_{c})}(t):={\sqrt {\mathrm {fb} }}\operatorname {sinc} ^{m}\left({\frac {t}{\mathrm {fb} ^{m}}}\right)e^{j2\pi f_{c}t}}
where sinc function that appears in Shannon sampling theorem.
m > 1 is the order of the spline fb is a bandwidth parameter fc is the wavelet center frequency The Shannon wavelet (sinc wavelet) is then clearly a special case of fbsp.
References S.G. Mallat, A Wavelet Tour of Signal Processing, Academic Press, 1999, ISBN 0-12-466606-X C.S. Burrus, R.A. Gopinath, H. Guo, Introduction to Wavelets and Wavelet Transforms: A Primer, Prentice-Hall, 1988, ISBN 0-13-489600-9. O. Cho, M-J. Lai, A Class of Compactly Supported Orthonormal B-Spline Wavelets in: Splines and Wavelets, Athens 2005, G Chen and M-J Lai Editors pp. 123–151. M. Unser, Ten Good Reasons for Using Spline Wavelets, Proc. SPIE, Vol.3169, Wavelets Applications in Signal and Image Processing, 1997, pp. 422–431.