Fourier theory made easy (?)

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5*sin (24t)

Amplitude = 5

Frequency = 4 Hz

seconds

A sine wave

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5*sin(24t)

Amplitude = 5

Frequency = 4 Hz

Sampling rate = 256 samples/second

seconds

Sampling duration =1 second

A sine wave signal

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-1.5

-1

-0.5

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1

1.5

2sin(28t), SR = 8.5 Hz

An undersampled signal

The Nyquist Frequency

• The Nyquist frequency is equal to one-half of the sampling frequency.

• The Nyquist frequency is the highest frequency that can be measured in a signal.

http://www.falstad.com/fourier/j2/

Fourier series

• Periodic functions and signals may be expanded into a series of sine and cosine functions

The Fourier Transform

• A transform takes one function (or signal) and turns it into another function (or signal)

The Fourier Transform

• A transform takes one function (or signal) and turns it into another function (or signal)

• Continuous Fourier Transform:

close your eyes if you don’t like integrals

The Fourier Transform

• A transform takes one function (or signal) and turns it into another function (or signal)

• Continuous Fourier Transform:

dfefHth

dtethfH

ift

ift

2

2

• A transform takes one function (or signal) and turns it into another function (or signal)

• The Discrete Fourier Transform:

The Fourier Transform

1

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1 N

n

Niknnk

N

k

Niknkn

eHN

h

ehH

Fast Fourier Transform

• The Fast Fourier Transform (FFT) is a very efficient algorithm for performing a discrete Fourier transform

• FFT principle first used by Gauss in 18??• FFT algorithm published by Cooley & Tukey in

1965• In 1969, the 2048 point analysis of a seismic trace

took 13 ½ hours. Using the FFT, the same task on the same machine took 2.4 seconds!

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Famous Fourier Transforms

Sine wave

Delta function

Famous Fourier Transforms

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0.5

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Gaussian

Gaussian

Famous Fourier Transforms

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1.5

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6

Sinc function

Square wave

Famous Fourier Transforms

Sinc function

Square wave

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1.5

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1

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4

5

6

Famous Fourier Transforms

Exponential

Lorentzian

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30

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0.2

0.4

0.6

0.8

1

FFT of FID

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f = 8 Hz SR = 256 HzT2 = 0.5 s

2exp2sin

Tt

fttF

FFT of FID

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f = 8 HzSR = 256 HzT2 = 0.1 s

FFT of FID

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f = 8 Hz SR = 256 HzT2 = 2 s

Effect of changing sample rate

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35

f = 8 Hz T2 = 0.5 s

Effect of changing sample rate

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SR = 256 HzSR = 128 Hz

f = 8 HzT2 = 0.5 s

Effect of changing sample rate

• Lowering the sample rate:– Reduces the Nyquist frequency, which– Reduces the maximum measurable frequency– Does not affect the frequency resolution

Effect of changing sampling duration

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f = 8 Hz T2 = .5 s

Effect of changing sampling duration

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ST = 2.0 sST = 1.0 s

f = 8 HzT2 = .5 s

Effect of changing sampling duration

• Reducing the sampling duration:– Lowers the frequency resolution– Does not affect the range of frequencies you

can measure

Effect of changing sampling duration

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f = 8 Hz T2 = 2.0 s

Effect of changing sampling duration

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ST = 2.0 sST = 1.0 s

f = 8 Hz T2 = 0.1 s

Measuring multiple frequencies

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f1 = 80 Hz, T21 = 1 s

f2 = 90 Hz, T22 = .5 s

f3 = 100 Hz, T2

3 = 0.25 s

SR = 256 Hz

Measuring multiple frequencies

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-2

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f1 = 80 Hz, T21 = 1 s

f2 = 90 Hz, T22 = .5 s

f3 = 200 Hz, T2

3 = 0.25 s

SR = 256 Hz

Some useful links

• http://www.falstad.com/fourier/– Fourier series java applet

• http://www.jhu.edu/~signals/– Collection of demonstrations about digital signal processing

• http://www.ni.com/events/tutorials/campus.htm– FFT tutorial from National Instruments

• http://www.cf.ac.uk/psych/CullingJ/dictionary.html– Dictionary of DSP terms

• http://jchemed.chem.wisc.edu/JCEWWW/Features/McadInChem/mcad008/FT4FreeIndDecay.pdf– Mathcad tutorial for exploring Fourier transforms of free-induction decay

• http://lcni.uoregon.edu/fft/fft.ppt– This presentation