The Fourer Series: An Analysis Of The Fourier Series

1515 Words4 Pages

Fourier series:
In the 18th century, the French mathematician Jean Bastiste Joseph Fourier made an extraordinary discovery; as a result of his investigation into partial differential equations modeling vibration and heat propagation in bodies, he found out that every function could be represented by an infinite series of sines and cosines (the basic trigonometric functions). For example the sound signal produced by any musical instruments such as piano, drums, etc. could be decomposed into its trigonometric constituents which reveals the fundamental frequencies that are combined to produce a specific sound. This idea of decomposing signals lies at the heart of modern electronic music; such as a synthesizer combines sine and cosine tones to …show more content…

It seems that the graph of S_n (x) is approaching the graph of f(x), with the exception when x=0 or x is an integer multiple of π.
The Fourier series of all kinds of signals and waveforms cannot be calculated. The function must satisfy some specific conditions known as the Dirichlet condition for convergence of Fourier series. These conditions are then used to define and prove the Fourier Convergence Theorem which gives the sum of the Fourier series. These conditions are that a periodic signal must be a piecewise continuous function, have finite number of extrema (maxima and/or minima) and have finite number of discontinuities (points in the function’s domain where the function is not continuous i.e. has a break).
Before going to prove the Convergence Theorem, some definitions of terms needs to be clarified. Periodic Function – A function f(x) is periodic with period T if for all the values of x, f(x+nT)=f(x), where T is a positive constant and n is an integer. For example, the sine function sin⁡x is periodic with the least period 2π and other periods such as -2π,4π,6π, …show more content…

Also at these points where f is discontinuous, the sum of Fourier series is the average of the left and the right limits, that is
1/2[f(a^+ )+f(a^- )]
And at any point where the function f is continuous,
1/2 [f(a^+ )+f(a^- )]=f(x)
It is quite evident that the Fourier Convergence theorem is quite effective and easier as it gives the partial sum of Fourier series without plotting the graph. For the above example (Fourier series of the square wave function) we observed that f(0^+ )=lim┬(x→0^+ )⁡〖f(x)〗=1 "and" f(0^- )=lim┬(x→0^- )⁡〖f(x)〗=0

The square wave function has discontinuities and the average of these left and right limits is 1⁄2, so for any integer n the Fourier Convergence Theorem says that
1/2+∑_(k=1)^∞▒〖2/((2k-1)π) sin⁡〖(2k-1)〗 x〗={█(f(x) "if" n≠nπ@1/2 "if "

More about The Fourer Series: An Analysis Of The Fourier Series

Open Document