Fourier Series Flashcards
fourier series is very useful for
describing phenomena with any kind of repeating, periodic behaviour.
Almost any kind of
periodic signal can be written as
sums of sines and cosines, or alternatively as exponentials.
for understanding fourier series, it is helpful to think of them as
a decomposition in
terms of orthogonal sets of vectors.
in the case of fourier series, the vectors are
functions
in the case of fourier series, the orthogonality is defined in terms of
a generalisation of the inner product of two vectors
inner product of vectors
<a|b>=a^cross b = sum for i=1 to N of ai^*bi
where cross denotes the hermitian conjugate and we have made us of Dirac notation
inner product of functions f and g
<f|g>= integral dx f(x)^*g(x)
for a scalar, the hermitian conjugate and the complex conjugate are
identical
proof for the functions sin(2πrx/L) and cos(2πrx/L) being the orthogonal basis vectors in the space of periodic functions with period L.
recognising odd and even functions
integrating an odd function gives zero
(one uses a trig identity)
fourier coefficients
a0, ar and br
depend on what specific function f(x) is being considered
how to obtain the cosone fourier coefficients
- using basis vector cos(2pipx/L) take the inner product with fourier series expansion
- consider each term and rearrange
the sine and cosine terms in a fourier series span
a vector space of functions
the fourier series for any function f(x) in the space, converges to
f(x) wherever f(x) is continuous
the fourier series of any function f(x) satisfies
the dirichlet conditions
the dirichlet conditions
- f(x) must be periodic
- f(x) must be single-valued and either continuous or with a finite number of finite discontinuities
- f(x) must be of bounded variation
- the integral over |f(x)| must converge