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This is not how we work here. We will gladly help you find the solution, but we won't do you work for you.merlyn said:Hi all. Could someone work out for me how equation 21 in attachment left side becomes right side. Please show in detail if you could.
It's for exponential Fourier series.
sophiecentaur said:@merlyn Have you tried any other sources? It's been a long time but is your problem with collapsing the product of two exponentials into one (with n-m in it) or doing the (trivial?) definite integral (∫eax dx) after that? Or is it the 1/(n-m) term on the RHS, when n=m?
The argument goes onto the next page of your book. What happens there?
General rule for multiplying exponentials: ##e^a e^b = e^{a+b}##.merlyn said:It's mainly collapsing the the two 'e' into one.
jtbell said:General rule for multiplying exponentials: ##e^a e^b = e^{a+b}##.
jtbell said:OK, so now you have the integral $$\int_0^L e^{i 2\pi (n-m) x/L} \, dx$$ Do you know how to integrate exponentials? The exponential looks messy, but it's just a big messy constant times x. Simplify it for a moment by collapsing the big messy constant into a new one, ##a = i 2\pi (n-m) /L##. Can you do this one? $$\int_0^L e^{ax} \, dx$$
Your presentation is very confusing. There is a button ∑ on the menu bar that gives you a whole selection of symbols - including πmerlyn said:Right..But that really does not help in this case.
All you get is ##e^(i2pinx-i2pimx)/l##
right?
and
##e^(i2pix(n-m))/l##
sophiecentaur said:Your presentation is very confusing. There is a button ∑ on the menu bar that gives you a whole selection of symbols - including π
sophiecentaur said:Your presentation is very confusing. There is a button ∑ on the menu bar that gives you a whole selection of symbols - including π
This is off topic, but I use the exact same edition.jtbell said:This made me dig in my closet to see if I still have my old book of math tables. Printed in 1986.
I can sympathise that you are out of touch with Calculus. If you really feel you need to get to grips with Fourier then it will be a long hard slog, I think. I can't recommend any particular learning resource but you will need more than just a list of integrals. The way many people look on Fourier is over simplified and they often come to wrong conclusions about what it really involves.merlyn said:I'll look up my integral tables tonight and see.
Thank you so far.
Ok.sophiecentaur said:I can sympathise that you are out of touch with Calculus. If you really feel you need to get to grips with Fourier then it will be a long hard slog, I think. I can't recommend any particular learning resource but you will need more than just a list of integrals. The way many people look on Fourier is over simplified and they often come to wrong conclusions about what it really involves.
A Fourier series equation is a mathematical representation of a periodic function as a sum of sine and cosine functions. It is used to describe the behavior of a periodic signal in terms of its fundamental frequency and its harmonics.
The derivation process for a Fourier series equation involves finding the coefficients of the sine and cosine terms by using the orthogonality properties of these functions. This is done by integrating the given periodic function over one period and using trigonometric identities to simplify the resulting equations.
The Fourier series equation is important because it allows us to analyze and understand the behavior of periodic signals, which are common in many areas of science and engineering. It also has practical applications in signal processing, image and sound compression, and data analysis.
The Fourier series equation has a wide range of applications in various fields, including physics, engineering, mathematics, and signal processing. Some common applications include analyzing the behavior of electrical circuits, predicting the behavior of vibrating systems, and compressing digital images and audio.
Yes, the Fourier series equation has some limitations. It can only be applied to periodic functions, and the function must be well-behaved (continuous and piecewise smooth). It also requires an infinite number of terms to accurately represent a function, which can be computationally expensive. Additionally, the Fourier series may not converge for certain types of functions, such as discontinuous or non-repeating functions.