Basic questions about signal processing and fourier analysis

In summary, a note is made up of a fundamental frequency and its harmonics. The fundamental frequency is usually the peak frequency, but not always. The first frequency is always the fundamental, and when looking up frequency tables, the given value is for the fundamental frequency.
  • #1
hale2bopp
21
0
1)A note consists of a fundamental frequency and the multiples of that frequency called harmonics. Peak frequency means that one that contributes most to the note. Is the fundamental frequency always the peak frequency? Since the frequencies die out very quickly as the value of n increases, where n is the factor that multiples the fundamental, shouldn't the fundamental always have the highest peak?
2)Is the first frequency always the fundamental?
3)When looking up frequency tables, there are specific numbers given for each note eg C3 has 63.5 Hz approx. What does this refer to? The peak, the fundamental, or some other value altogether?
Thanks!
 
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  • #2
I assume you are asking about sound.

1) Most likely, but not always.
2) Yes.
3) Table will give value for fundamental.
 
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Related to Basic questions about signal processing and fourier analysis

1. What is signal processing and why is it important?

Signal processing is the analysis, manipulation, and interpretation of signals to extract information or enhance their quality. It is important because it allows us to extract useful information from signals, such as audio, images, and data, and to improve their quality for various applications.

2. What is the Fourier transform and how does it relate to signal processing?

The Fourier transform is a mathematical tool used to decompose a signal into its constituent frequencies. It relates to signal processing because it allows us to analyze signals in the frequency domain, which can provide valuable insights and help with tasks such as noise reduction and filtering.

3. What is the difference between discrete and continuous signals?

A continuous signal is a signal that exists and can be measured at every point in time, while a discrete signal is a signal that is only defined at specific points in time. In signal processing, we often work with discrete signals, as they are easier to analyze and manipulate.

4. How does sampling rate affect signal processing?

The sampling rate is the number of samples taken from a continuous signal per unit time. It affects signal processing because if the sampling rate is too low, important information from the signal may be lost, leading to distorted outputs. It is important to choose an appropriate sampling rate based on the signal's bandwidth and the desired level of accuracy.

5. What are some common applications of signal processing and Fourier analysis?

Signal processing and Fourier analysis have a wide range of applications, including image and audio processing, speech recognition, data compression, and communication systems. They are also used in fields such as medicine, astronomy, and engineering for tasks such as signal denoising, pattern recognition, and system identification.

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