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In [[mathematics]], '''Fourier–Bessel series''' is a particular kind of [[generalized Fourier series]] (an [[infinite series]] expansion on a finite interval) based on [[Bessel function]]s.
 
Fourier–Bessel series are used in the solution to [[partial differential equation]]s, particularly in [[cylindrical coordinate]] systems.
 
== Definition ==
 
The Fourier–Bessel series of a function ''f(x)'' with a [[Domain of a function|domain]] of [0,b]
 
:<math>f: [0,b] \rightarrow \mathbb{R}</math>
 
is the notation of that function as a [[linear combination]] of many [[orthogonal]] versions of the same [[Bessel functions of the first kind|Bessel function of the first kind]] ''J''<sub>α</sub>, where the argument to each version ''n'' is differently scaled, according to
 
:<math>(J_\alpha )_n (x) := J_\alpha \left( \frac{u_{\alpha,n}}b x \right)</math>
 
where ''u''<sub>α,n</sub> is a [[Root of a function|root]], numbered ''n'' associated with the Bessel-Function ''J''<sub>α</sub> and ''c''<sub>n</sub> are the assigned coefficients:
 
:<math>f(x) \sim \sum_{n=0}^\infty c_n J_\alpha \left( \frac{u_{\alpha,n}}b x \right)</math>.
 
== Interpretation ==
 
The Fourier–Bessel series may be thought of as a Fourier expansion in the ρ coordinate of [[cylindrical coordinates]]. Just as the [[Fourier series]] is defined for a finite interval and has a counterpart, the [[continuous Fourier transform]] over an infinite interval, so the Fourier–Bessel series has a counterpart over an infinite interval, namely the [[Hankel transform]].
 
== Calculating the coefficients ==
 
Because said, differently scaled Bessel Functions are orthogonal with respect to the [[inner product]]
 
:<math>\langle f,g \rangle = \int_0^b  x f(x) g(x) \mathrm{d}x</math>
 
according to
 
:<math>\int_0^1 x J_\alpha(x u_{\alpha,n})\,J_\alpha(x u_{\alpha,m})\,dx
= \frac{\delta_{mn}}{2} [J_{\alpha+1}(u_{\alpha,n})]^2</math>,
 
the coefficients can be obtained from [[Vector projection|projecting]] the function ''f(x)'' onto the respective Bessel functions:
 
:<math>c_n = \frac{ \langle f,(J_\alpha)_n \rangle }{ \langle (J_\alpha)_n,(J_\alpha)_n \rangle } = \frac{ \int_0^b  x f(x) (J_\alpha)_n(x) \mathrm{d}x }{ \frac12 (b(J_{\alpha\pm1})_n(b))^2}</math>
 
where the plus or minus sign is equally valid.
 
== Application ==
 
The Fourier–Bessel series expansion employs aperiodic and decaying Bessel functions as the basis. The Fourier–Bessel series expansion has been successfully applied in diversified areas such as Gear fault diagnosis, discrimination of odorants in a turbulent ambient, postural stability analysis, detection of voice onset time, glottal closure instants (epoch) detection, separation of speech formants, EEG signal segmentation, speech enhancement, and speaker identification. The Fourier–Bessel series expansion has also been used to reduce cross terms in the Wigner–Ville distribution.
 
==Dini series==
 
A second Fourier–Bessel series, also known as ''Dini series'', is associated with the [[Robin boundary condition]]
:<math>b f'(b) + c f(b) = 0 </math>, where <math>c</math> is an arbitrary constant.
The Dini series can be defined by
:<math>f(x) \sim \sum_{n=0}^\infty b_n J_\alpha(\gamma_n x/b)</math>,
 
where <math>\gamma_n</math> is the ''n''th zero of <math>x J'_\alpha(x)+cJ_\alpha(x)</math>.
 
The coefficients <math>b_n</math> are given by
 
:<math>
b_n = \frac{2 \gamma_n^2}{ b^2(c^2+\gamma_n^2-\alpha^2)J_\alpha^2(\gamma_n)}
\int_{0}^b J_\alpha(\gamma_n x/b)\,f(x) \,x\,dx
</math>.
 
==References==
 
* {{cite book |last=Smythe|first=William R.|title=Static and Dynamic Electricity |edition=3rd |publisher=McGraw-Hill|location=New York|year=1968}}
 
* {{cite book | last1 = Magnus | first1 = Wilhelm | last2 = Oberhettinger | first2 = Fritz | last3 = Soni | first3 = Raj Pal | title = Formulas and Theorems for Special Functions of Mathematical Physics | year = 1966 | publisher = [[Springer Science+Business Media|Springer]] | location = Berlin }}
 
* J. Schroeder, Signal processing via Fourier–Bessel series expansion, Digital Signal Process. 3 (1993), 112–124.
 
* G. D’Elia, S. Delvecchio and G. Dalpiaz, On the use of Fourier–Bessel series expansion for gear diagnostics, Proc. of the Second Int. Conf. Condition Monitoring of Machinery in Non-Stationary Operations (2012), 267-275.
 
* A. Vergaraa, E. Martinelli, R. Huerta, A. D’Amico and C. Di Natale, Orthogonal decomposition of chemo-sensory signals: Discriminating odorants in a turbulent ambient, Procedia Engineering 25 (2011), 491–494.
 
* F.S. Gurgen and C. S. Chen, Speech enhancement by Fourier–Bessel coefficients of speech and noise, IEE Proc. Comm. Speech Vis. 137 (1990), 290–294.
 
* K. Gopalan, T. R. Anderson and E. J. Cupples, A comparison of speaker identification results using features based on cepstrum and Fourier–Bessel expansion, IEEE Trans. Speech Audio Process. 7 (1999), 289–294.
 
==External links==
* {{springer|title=Fourier-Bessel series|id=p/f041000}}
* {{cite web| last = Weisstein | first = Eric. W | authorlink = Eric W. Weisstein | title = Fourier-Bessel Series | work = From [[MathWorld]]--A Wolfram Web Resource | url = http://mathworld.wolfram.com/Fourier-BesselSeries.html }}
* Fourier–Bessel series applied to Acoustic Field analysis on [http://www.trinnov.com/en/about-us/research/overview Trinnov Audio's research page]
 
==See also==
*[[Orthogonality]]
*[[Generalized Fourier series]]
*[[Hankel transform]]
*[[Neumann polynomial]]
*
 
{{DEFAULTSORT:Fourier-Bessel series}}
[[Category:Fourier series]]

Latest revision as of 21:12, 15 September 2013

In mathematics, Fourier–Bessel series is a particular kind of generalized Fourier series (an infinite series expansion on a finite interval) based on Bessel functions.

Fourier–Bessel series are used in the solution to partial differential equations, particularly in cylindrical coordinate systems.

Definition

The Fourier–Bessel series of a function f(x) with a domain of [0,b]

f:[0,b]

is the notation of that function as a linear combination of many orthogonal versions of the same Bessel function of the first kind Jα, where the argument to each version n is differently scaled, according to

(Jα)n(x):=Jα(uα,nbx)

where uα,n is a root, numbered n associated with the Bessel-Function Jα and cn are the assigned coefficients:

f(x)n=0cnJα(uα,nbx).

Interpretation

The Fourier–Bessel series may be thought of as a Fourier expansion in the ρ coordinate of cylindrical coordinates. Just as the Fourier series is defined for a finite interval and has a counterpart, the continuous Fourier transform over an infinite interval, so the Fourier–Bessel series has a counterpart over an infinite interval, namely the Hankel transform.

Calculating the coefficients

Because said, differently scaled Bessel Functions are orthogonal with respect to the inner product

f,g=0bxf(x)g(x)dx

according to

01xJα(xuα,n)Jα(xuα,m)dx=δmn2[Jα+1(uα,n)]2,

the coefficients can be obtained from projecting the function f(x) onto the respective Bessel functions:

cn=f,(Jα)n(Jα)n,(Jα)n=0bxf(x)(Jα)n(x)dx12(b(Jα±1)n(b))2

where the plus or minus sign is equally valid.

Application

The Fourier–Bessel series expansion employs aperiodic and decaying Bessel functions as the basis. The Fourier–Bessel series expansion has been successfully applied in diversified areas such as Gear fault diagnosis, discrimination of odorants in a turbulent ambient, postural stability analysis, detection of voice onset time, glottal closure instants (epoch) detection, separation of speech formants, EEG signal segmentation, speech enhancement, and speaker identification. The Fourier–Bessel series expansion has also been used to reduce cross terms in the Wigner–Ville distribution.

Dini series

A second Fourier–Bessel series, also known as Dini series, is associated with the Robin boundary condition

bf(b)+cf(b)=0, where c is an arbitrary constant.

The Dini series can be defined by

f(x)n=0bnJα(γnx/b),

where γn is the nth zero of xJ'α(x)+cJα(x).

The coefficients bn are given by

bn=2γn2b2(c2+γn2α2)Jα2(γn)0bJα(γnx/b)f(x)xdx.

References

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  • 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

    My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
  • J. Schroeder, Signal processing via Fourier–Bessel series expansion, Digital Signal Process. 3 (1993), 112–124.
  • G. D’Elia, S. Delvecchio and G. Dalpiaz, On the use of Fourier–Bessel series expansion for gear diagnostics, Proc. of the Second Int. Conf. Condition Monitoring of Machinery in Non-Stationary Operations (2012), 267-275.
  • A. Vergaraa, E. Martinelli, R. Huerta, A. D’Amico and C. Di Natale, Orthogonal decomposition of chemo-sensory signals: Discriminating odorants in a turbulent ambient, Procedia Engineering 25 (2011), 491–494.
  • F.S. Gurgen and C. S. Chen, Speech enhancement by Fourier–Bessel coefficients of speech and noise, IEE Proc. Comm. Speech Vis. 137 (1990), 290–294.
  • K. Gopalan, T. R. Anderson and E. J. Cupples, A comparison of speaker identification results using features based on cepstrum and Fourier–Bessel expansion, IEEE Trans. Speech Audio Process. 7 (1999), 289–294.

External links

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  • Template:Cite web
  • Fourier–Bessel series applied to Acoustic Field analysis on Trinnov Audio's research page

See also