Howtosignalprocessing
- What are the problems with polynomial interpolation for large number of data set?
- What are the advantages of upsampling?
- What happens in upsampling?
- What is upsampling and downsampling?
What are the problems with polynomial interpolation for large number of data set?
The main problem with polynomial interpolation arises from the fact that even when a certain polynomial function passes through all known data points, the resulting graph might not reflect the actual state of affairs.
What are the advantages of upsampling?
Converting a digital (sampled) signal to a continuous analogue waveform requires interpolation to produce the values between sample points. Doing part of this interpolation digitally (upsampling) simplifies the analogue circuitry and gives better results. That's all there is to it.
What happens in upsampling?
Upsampling is the process of inserting zero-valued samples between original samples to increase the sampling rate. (This is sometimes called “zero-stuffing”.) This kind of upsampling adds undesired spectral images to the original signal, which are centered on multiples of the original sampling rate.
What is upsampling and downsampling?
Downsampling, which is also sometimes called decimation, reduces the sampling rate. Upsampling, or interpolation, increases the sampling rate. Before using these techniques you will need to be aware of the following.
