| Line 11: | Line 11: | ||
When there are only 1 non-zero term, the time and frequency domain are shown below: | When there are only 1 non-zero term, the time and frequency domain are shown below: | ||
| − | + | <gallery> | |
| + | File:time1.jpeg|1.time | ||
| + | File:1freq.jpg|1.freq | ||
| + | </gallery> | ||
When 2 non-zero terms | When 2 non-zero terms | ||
| + | |||
| + | <gallery> | ||
| + | File:time2.jpg|2.time | ||
| + | File:freq2.jpg|2.freq | ||
| + | </gallery> | ||
When 5 non-zeros terms | When 5 non-zeros terms | ||
| + | |||
| + | <gallery> | ||
| + | File:time5.jpg|5.time | ||
| + | File:freq5.jpg|5.freq | ||
| + | </gallery> | ||
When there are 25 non-zero terms | When there are 25 non-zero terms | ||
| + | |||
| + | <gallery> | ||
| + | File:time25.jpg|25.time | ||
| + | File:freq25.jpg|25.freq | ||
| + | </gallery> | ||
Revision as of 15:29, 21 April 2018
Approximating Periodic Signals with Finite Fourier Series
In this project, a matlab function will be used to show how a finite number of Fourier Series coefficients can approximate a periodic signal.
square.m
When there are only 1 non-zero term, the time and frequency domain are shown below:
1.time
1.freq
When 2 non-zero terms
2.time
2.freq
When 5 non-zeros terms
5.time
5.freq
When there are 25 non-zero terms
25.time
25.freq
Conclusion: From the above diagrams we are able to distinguish that: As the number of Fourier Series Coefficients increases, the output of approximated periodic signal is more accurate.
A circuit is built to measure the Fourier series of a Square wave
For example, we set s(t) to be square wave with A = 3V, T0 = 0.5*10^-6s The frequency domain of output shown in spectrum analyzer will be:
The time domain of output shown in oscilloscope will be:
