how can i found some information about fourier application?
366137
http://csdl2.computer.org/persagen/DLAbsToc.jsp?resourcePath=/dl/proceedings/&toc=comp/proceedings/icip/1995/7310/03/7310toc.xml&DOI=10.1109/ICIP.1995.537702
81441
Two reasons:\n1. Because it results in a finite spectrum result for a signal. Fourier Transform typically results in infinite spectrum result for a function (e.g if the function has C1 or C0 discontinuities e.g. square wave, triangular wave, ramp, sawtooth)\n\n2. FT assumes that signals are "stationary" and that their frequency-domain can be computed over infinite-time window and will not change. This is unrealistic - most real-world signals are not stationary in a window >10ms (e.g. speech, telecomms, EKG). WT computes its transform based on both a time- and frequency-window.\n\nAs to why you compute DWT rather than the direct Continuous (integral formulation) WT, it's for the same simple reason you generally use DFT instead of CFT - because it's mathematically tractable and lends itself to efficient digital computation (order(NlogN) time); also this formulation can be very efficiently parallelised whether in hardware or software esp. if N is a power of 2 e.g. 64,256,512,1024,... and people have developed these implementations very far (they're a standard toolbox feature or hardware IP).\n\nI don't know the theoretical links offhand but they should be trivial to find.
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http://www.wolfram.com/webresources.html
556680
http://en.wikipedia.org/wiki/Modulation_index
676950
A few that come to mind at Euler, Maxima and Octave. Unfortunately, I don't think any of the free packages come close to Mathematica or Matlab, but maybe one of them will still meet your needs.
730722
put sinx=t\ncosxdx=dt\nI=fcos(pi t)dt with limits -1,+1\nI=(sin(pi t))/pi with limits +1,-1\nI=(sin(pi)-sin(-pi))/pi=0\nthanks & good luck
601386
Through the fourier map generator.
849482
Have you thought about using FFT (Fast Fourier Transform)? That should be easy to implement.
13310
It's the limit of a type of convergent infinite sum (that's why it's symbol is an elongated 's').\n\nIt's applications range from finding the solutions to differential equations, being used to calculate an area, volume (in the sense we know it, and in a generalised space of n-dimensions).  In Fourier Analysis it's used to approximate functions using cos and sin, etc.  But, by far, the best use of it has to be answering exam questions.\n\nNot helpful, but fairly interesting.  So I thought.  I'll go now.
774228
Try Infranview http://www.irfanview.com/ its free
245242
I use AWstats (http://awstats.sourceforge.net/).  It's free and gives you all sorts of info.  It requires Perl to be installed but it's not bad and there are plenty of tutorials on google.
501273
Didn't got the question do you want the solution for all the problems of goodman's Introduction to Fourier optics book? Well I do not think I have them any more if you want a specific problem I can help you. I can even try to get a chapter solution for you. Just tell me each one, I can try to get it for you, I do not garantee but I think I may have a way to got them just send me an email (I have a yahoo email). If you have the solutions and you don't understand tell me each problem I can do it in more detail probably, not garantee at 100% but at a good 90% .
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try this one:\n\nhttp://onin.com/fp/afis/afis.html
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if u have \n\nt=1:2:1000\n\nS =10sin30t\n\nplot(S)\n\nFs=fft(S,512)\n\nplot(Fs) \n\n\nso if u have any signal it will be stored in vector on the matlab .. like .. X= 155x1 matrix size\n\njust convert the X by\n\nXftt= fft(X)\nor\nXfft2=ffft2(X)\nplot(Xfft)\npause\nplot (Xfft)\n\n\nand anything u want u can use matlab help it is v cool \n\n\ni wish i could help u
142496
There are a number of available tools in the following website:\n\nhttp://www.functionx.com/
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this maybe helpful \n\n\n\nwww.springerlink.com/index/R617G25W81437Q01.pdf\n\nhttp://www.springerlink.com/index/R617G25W81437Q01.pdf
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One of the beauties when using Fourier transforms, is the ability to work with a spectrum of modes and act on each of the components individually with a filter. By sampling the function over a period  with a finite number of values  , where  is the size of the sampling interval, the spectrum gets truncated at the shortest wavelength  called Nyquist critical wavelength: this corresponds to exactly 2 mesh points per wavelength, which does however not mean that shorter wavelengths  do not contribute to the Fourier coefficients (4.1#eq.1). Figure 4.3#fig.1 illustrates how they get aliased back into the lower components of the spectrum