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Full Version: Spectral Analysis: Fourier Series
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INTRODUCTION
function by decomposing it into a weighted sum of much simpler sinusoidal component functions sometimes referred to as normal Fourier modes, or simply modes for short. The weights, or coefficients, of the modes, are a one-to-one mapping of the original function. These modal coefficients are sometimes themselves confusingly referred to as "modes" for brevity, especially in physics literature. Fourier series serve many useful purposes, as manipulation and conceptualization of the modal coefficients are often easier than with the original function.
Areas of application include electrical engineering, vibration analysis, acoustics, optics, signal and image processing, and data compression. Using the tools and techniques of spectroscopy, for example, astronomers can deduce the chemical composition of a star by analyzing the frequency components, or spectrum, of the star's emitted light. Similarly, engineers can optimize the design of a telecommunications system using information about the spectral components of the data signal that the system will carry. See also spectrum analyzer.
Who is Fourier?
 Fourier is one of the France’s greatest administrators, historians, and mathematicians.
 He graduated with honors from the military school in Auxerre and became a teacher of math when he was 16 years old.
 Later he joined the faculty at Ecole Normale and then the Polytechnique in Paris when he is 27.
 He went to Egypt with Napoleon as the Governor of Lower Egypt after the 1798 Expedition.
 He was secretary of the Academy of Sciences in 1816 and Fellow in 1817.
Lord Kelvin on Fourier’s theorem
Fourier’s theorem is not only one of the most beautiful results of modern analysis, but it may be said to furnish an indispensable instrument in the treatment of nearly every recondite question in modern physics.
Fourier’s basic idea
Trigonometric functions: sin(x) and cos(x) has the period 2π.sin(nx) and cos(nx) have period 2π/n.The linear combination of these functions or multiply each by a constant, the adding result still has a period 2π.
Fourier series
• Fourier series: a complicated waveform analyzed into a number of harmonically related sine and cosine functions.A continuous periodic signal x(t) with a period T0 may be represented by:
• Dirichlet conditions must be placed on x(t) for the series to be valid: the integral of the magnitude of x(t) over a complete period must be finite, and the signal can only have a finite number of discontinuities in any finite interval
Trigonometric form for Fourier series:
• If the two fundamental components of a periodic signal are B1cosω0t and C1sinω0t, then their sum is expressed by trigonometric identities:
• If this procedure is applied to all the harmonic components of a Fourier series:
Fourier Series


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Just before 1800, the French mathematician/physicist/engineer Jean Baptiste Joseph
Fourier made an astonishing discovery. As a result of his investigations into the partial dif-
ferential equations modeling vibration and heat propagation in bodies, Fourier was led to
claim that “every” function could be represented by an infinite series of elementary trigono-
metric functions — sines and cosines. As an example, consider the sound produced by a
musical instrument, e.g., piano, violin, trumpet, oboe, or drum. Decomposing the signal
into its trigonometric constituents reveals the fundamental frequencies (tones, overtones,
etc.) that are combined to produce its distinctive timbre. The Fourier decomposition lies
at the heart of modern electronic music; a synthesizer combines pure sine and cosine tones
to reproduce the diverse sounds of instruments, both natural and artificial, according to
Fourier’s general prescription.
Fourier’s claim was so remarkable and unexpected that most of the leading mathe-
maticians of the time did not believe him. Nevertheless, it was not long before scientists
came to appreciate the power and far-ranging applicability of Fourier’s method, thereby
opening up vast new realms of physics, engineering, and elsewhere, to mathematical anal-
ysis. Indeed, Fourier’s discovery easily ranks in the “top ten” mathematical advances of
all time, a list that would include Newton’s invention of the calculus, and Gauss and Rie-
mann’s establishment of differential geometry that, 70 years later, became the foundation
of Einstein’s general relativity.



Dynamical Equations of Continuous Media.

The purpose of this section is to discover why Fourier series arise naturally when
we move from discrete systems of ordinary differential equations to the partial differential
equations that govern the dynamics of continuous mechanical systems. In our reconstrucd-
tion of Fourier’s thought processes, let us start by reviewing what we have learned.
In Chapter 6, we characterized the equilibrium equations of discrete mechanical and
electrical systems as a linear algebraic system