quickconverts.org

Fourier Sine Series Of Cos X

Image related to fourier-sine-series-of-cos-x

Decoding the Fourier Sine Series of cos(x): A Simplified Approach



Trigonometric functions, like sine and cosine, are fundamental building blocks in describing periodic phenomena, from sound waves to the oscillations of a pendulum. The Fourier series is a powerful mathematical tool that allows us to represent any periodic function as a sum of sine and cosine functions. This article focuses specifically on finding the Fourier sine series of cos(x), a seemingly counterintuitive task since cos(x) is inherently an even function, while the sine series is designed for odd functions. We'll unravel this apparent paradox step-by-step.

1. Understanding Fourier Sine Series



The Fourier sine series represents a function f(x) defined on the interval [0, L] as an infinite sum of sine functions:

f(x) ≈ a₁sin(πx/L) + a₂sin(2πx/L) + a₃sin(3πx/L) + ... = Σ[aₙsin(nπx/L)] (n=1 to ∞)

where the coefficients aₙ are given by:

aₙ = (2/L) ∫₀ᴸ f(x)sin(nπx/L) dx

This formula essentially decomposes f(x) into its constituent sine wave frequencies. Crucially, this series only works for functions defined on [0, L] and implicitly assumes an odd extension of f(x) to the interval [-L, L]. That means we reflect the function about the y-axis, making it odd.

2. The Odd Extension of cos(x)



The key to finding the Fourier sine series of cos(x) lies in understanding its odd extension. While cos(x) itself is an even function (symmetrical about the y-axis), we force it to be odd by considering only the interval [0, π] (we choose L=π for simplicity) and then reflecting it across the y-axis to create an odd function on [-π, π]. This odd extension, let's call it g(x), will be different from cos(x) on the entire interval [-π, π].

Specifically, on [0, π], g(x) = cos(x), but on [-π, 0], g(x) = -cos(x). This is a crucial step because the Fourier sine series inherently works with odd functions.

3. Calculating the Coefficients



Now we can apply the formula for aₙ using our odd extension g(x):

aₙ = (2/π) ∫₀ᴨ cos(x)sin(nx) dx

This integral can be solved using integration by parts or trigonometric identities. Employing trigonometric identities, we can rewrite cos(x)sin(nx) as:

cos(x)sin(nx) = ½[sin((n+1)x) - sin((n-1)x)]

Integrating this over [0, π] yields:

aₙ = (1/π) [(cos(0) - cos((n+1)π))/(n+1) - (cos(0) - cos((n-1)π))/(n-1)] for n ≠ 1

For n = 1:

a₁ = (2/π) ∫₀ᴨ cos(x)sin(x) dx = (1/π) ∫₀ᴨ sin(2x) dx = 0

For n > 1 and n even, aₙ = 0. For n odd (n ≥ 3), aₙ = 4/[π(n²-1)](-1)^[(n-1)/2].

Therefore, the Fourier sine series of cos(x) on [0, π] is:

cos(x) ≈ Σ[aₙsin(nx)] (n=1 to ∞) , with aₙ defined as above.


4. Practical Example and Interpretation



Let's say we want to approximate cos(x) using the first three terms of its Fourier sine series. We calculate a₃, a₅, and a₇ using the formula derived above, and plug them into the series. The resulting approximation will be a sum of sine waves which, surprisingly, resembles cos(x) on the interval [0, π]. Note that the approximation will deviate significantly outside this interval, as it's built upon the odd extension.

5. Key Takeaways



The Fourier sine series of cos(x) is not a direct representation of cos(x) itself. Instead, it's a representation of the odd extension of cos(x) on a specific interval. This highlights the importance of understanding the underlying assumptions and limitations of Fourier series expansions. The result is a sum of sine functions that approximates cos(x) only on the interval [0, π], demonstrating the power and limitations of this powerful analytical tool.


FAQs:



1. Why do we use an odd extension for the Fourier sine series? The Fourier sine series is inherently designed to represent odd functions. By creating an odd extension, we're forcing cos(x) to fit this framework, allowing us to apply the sine series formula.

2. Can we use a cosine series instead? Yes, the Fourier cosine series is ideal for representing even functions directly, so using that for cos(x) would be a more straightforward approach.

3. What happens outside the interval [0, π]? The Fourier sine series, based on the odd extension, will accurately represent the odd extension of cos(x) on [-π, π]. It won't represent cos(x) itself outside this interval.

4. How accurate is the approximation? The accuracy increases as more terms are included in the series. However, due to the Gibbs phenomenon, there will always be some overshoot near discontinuities (in this case, at the edges of the interval).

5. What are the applications of this? While directly representing cos(x) using sine series might seem odd, the concept illustrates the flexibility of Fourier series and their application to solving problems where only half of the periodic function is known, or where an odd representation is needed for specific problem contexts (e.g., certain heat transfer problems).

Links:

Converter Tool

Conversion Result:

=

Note: Conversion is based on the latest values and formulas.

Formatted Text:

478cm to inches convert
18 cm to in convert
17cm in convert
395 cm convert
117cm in inches convert
167 cm to inches convert
126 cm in inches convert
109 cm to inches convert
628 cm to inches convert
189cm to inches convert
81 cm in inches convert
32 centimetros en pulgadas convert
453 cm to inches convert
27 centimetros en pulgadas convert
3 4 cm in inches convert

Search Results:

What are the limitations /shortcomings of Fourier Transform and … 5 May 2015 · Here is my biased and probably incomplete take on the advantages and limitations of both Fourier series and the Fourier transform, as a tool for math and signal processing.

傅里叶变换(Fourier Transform) - 知乎 24 Apr 2020 · 傅里叶变换(Fourier transform)是一种线性积分变换,用于信号在时域和频域之间的变换。而快速傅里叶变换 (Fast Fourier Transform,FFT), 是一种可在O(nlogn)时间内 …

How to calculate the Fourier transform of a Gaussian function? In the QM context, momentum and position are each other's Fourier duals, and as you just discovered, a Gaussian function that's well-localized in one space cannot be well-localized in …

How to calculate the Fourier Transform of a constant? How to calculate the Fourier Transform of a constant? Ask Question Asked 11 years, 2 months ago Modified 6 years ago

Fourier Transform on positive real line - Mathematics Stack … 24 Jan 2018 · The natural transform to apply on the half line is the Laplace Transform. Typically Fourier transform is applied on the whole line and Fourier Series to finite intervals.

Fourier Series of a Constant Function - Mathematics Stack … In a normal Fourier series one can shift it up or down with this constant term a0 a 0. However, in this case, the constant term is all you need: you just put f(x) =a0 = 5 f (x) = a 0 = 5 and make …

What is the Fourier transform of $f(t)=1$ or simply a constant? 6 May 2017 · 1 I know that this has been answered, but it's worth noting that the confusion between factors of 2π 2 π and 2π−−√ 2 π is likely to do with how you define the Fourier …

Fourier Transform of Derivative - Mathematics Stack Exchange Fourier transform commutes with linear operators. Derivation is a linear operator. Game over.

What is the Fourier transform of the product of two functions? Transforms such as Fourier transform or Laplace transform, takes a product of two functions to the convolution of the integral transforms, and vice versa. This is called the Convolution …

Fourier transform for dummies - Mathematics Stack Exchange What is the Fourier transform? What does it do? Why is it useful (in math, in engineering, physics, etc)? This question is based on the question of Kevin Lin, which didn't quite fit in Mathoverflow.