09. Interpolation in Review

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Interpolation in Review

Interpolation is a technique to estimate a signal at points in time between existing samples. We can use this technique to normalize a signal that was sampled non-uniformly. We can also use it to resample a signal when comparing signals that are sampled at different sampling rates. Resampling is the process of changing the sampling rate of a discrete signal.

Linear Interpolation

QUESTION:

Timestamp (ms) Value
1000 30
1250 40
1500 42
Using linear interpolation, what would the value of the above time-series signal be at timestamp 1200?

SOLUTION:

These answers need to be solved by yourself, I believe you can do it

vocab

New Vocabulary

  • Interpolation: A method for estimating new data points within a range of discrete known data points.
  • Resampling: The process of changing the sampling rate of a discrete signal to obtain a new discrete representation of the underlying continuous signal.

Resampling exercise intro

Exercise 2: Interpolation

Instructions

  1. Complete the Offline or Online instructions below.
  2. Read through the whole .ipynb.
  3. Complete all the code cells that contain ## Your Code Goes Here.

Offline

  1. In the repo which you can access here in the repo /intro-to-dsp/exercises/2-interpolation/ you should find the following files:
    • 2_interpolation.ipynb
    • exercise2.npz
  2. Open up the python notebook and associated files in your desired editor.

Note: Instructions can be found in Introduction to Wearable Data's Concept Developer Workflow for how to set up your local environment.

Online

  1. Go to the next concept and the 2_interpolation.ipynb should be open and the workspace should already contain the appropriate exercise2.npz file.

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