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Sensors (Sensor definition (E.g. (Barometer: measure air pressure -…

- - - - Binary
      - On when above, off when below
      - On when above higher threshold, off when below lower threshold
    - - for each window, calculate mean value
      - Larger window => larger lag + more smooth on straight lines + worse for edges
      - Negative
        
        more susceptible to outliers
        
        must wait for window to fill (laggy)
        
        No dynamic model
      - Positive
        
        easy to calculate (uniform mean or weighted mean with more weights on more recent calculations)
        
        Efficient
        
        Great cost-benefit
      - Assume trajectory is smooth
    - - for each window, calculate median value
      - Negative
        
        Must wait for window to fill (laggy)
        
        No dynamic model
      - Positive
        
        Less susceptible to outliers
        
        Does not make up data
        
        Efficient
        
        Easy to implement
        
        Great cost-benefit
      - Larger window => larger lag + more smooth on straight lines + represent edges better than mean filters
      - Assume trajectory is smooth
    - - Makes assumptions about behaviour
      - Predict the next step; use the measure in the present to adjust the underlying model
      - Diagram 10
      - Positives
        
        Dynamic model of the system
        
        No lag
        
        Tunable trade-off between model and measurement
        
        Uncertainty estimate
        
        Cheap to run
      - Negatives
        
        Parameters not intuitive
        
        Overshooting
      - Assumptions
        
        Bayesian model for future state
        
        Gaussian model for noises (strong assumption)
        
        Linear for noises (strong assumption)
        
        Online
      - Kalmn gain ratio
        
        Higher: use more recent measurements.
        
        Lower: use recent predictions
    - - generate hypotheses
      - Compute weights
      - resample; generate random numbers
      - Positives
        
        General
        
        Continuous or discrete variables
        
        Great results
      - Negatives
        
        Lots of memory
        
        Very slow