Answers.Body: <ul>
  <li><strong>Cross correlation</strong>
  A high cross-correlation value indicates a strong correlation between the two signals, which can be useful for identifying the specific event that one of the signals is sensitive to.</li>
  <li><strong>TimeLag</strong>
  Which represents the time delay between the occurrence of the event in one signal and its effect on the other signal.</li>
  <li><strong>Frequency</strong> <strong>Analysis</strong>
  This can be useful for identifying any periodicities or cycles in the signals that may be related to the specific event.</li>
  <li><strong>Statistical</strong> <strong>Analysis</strong>
  You can perform various statistical analyses of the two signals, such as mean, median, variance, and standard deviation, to compare their overall characteristics.</li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-04-17T09:57:14.750Z
Answers.LastActivityDate: 2023-04-17T09:57:14.750Z
Answers.UserDisplayName: Joypal
Body: <p>i have two temperature signals from which one is sensitive toward a specific event. I would like to know what other features can be useful to extract apart from:</p>
  <ol>
  <li>Angles (between the two).</li>
  <li>Slopes ( between the two).</li>
  </ol>
  <p>P.S. Language is Python</p>
  
Tags: <python><time-series><feature-extraction><feature-engineering>
Title: Feature Extraction for timeseries temperature signal
UserDisplayName: Mirza
ThreadText: # Feature Extraction for timeseries temperature signal
  
  (Asked by: username_0 on 2023-04-17)
  
  i have two temperature signals from which one is sensitive toward a specific event. I would like to know what other features can be useful to extract apart from:
  
  1. Angles (between the two).
  2. Slopes ( between the two).
  
  P.S. Language is Python
  
  **Tags:** python, time-series, feature-extraction, feature-engineering
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2023-04-17. Score: 1
  
  * **Cross correlation**
    A high cross-correlation value indicates a strong correlation between the two signals, which can be useful for identifying the specific event that one of the signals is sensitive to.
  * **TimeLag**
    Which represents the time delay between the occurrence of the event in one signal and its effect on the other signal.
  * **Frequency** **Analysis**
    This can be useful for identifying any periodicities or cycles in the signals that may be related to the specific event.
  * **Statistical** **Analysis**
    You can perform various statistical analyses of the two signals, such as mean, median, variance, and standard deviation, to compare their overall characteristics.
  
  
  ---
  
  