Gaussian Filter
3 min
the gaussian filter processor smooths a signal using a gaussian (bell curve) weighting function why use gaussian filter use this processor to reduce noise in a signal while preserving its underlying trend, for example, smoothing a noisy sensor reading before it reaches a dashboard or a downstream calculation how it works the processor calculates the mean and standard deviation of the current window of values, then uses them to weight the current value values closer to the window's mean carry more weight, and values farther from it carry less specifically, it calculates a coefficient as 1 / (sqrt(2π) × standard deviation) and an exponential term as exp( 1/2 × (current mean)² / standard deviation²) multiplying the coefficient by the exponential term gives the filtered value if your input tag doesn't publish at a steady rate, use timer interval to publish a value on a fixed schedule instead of waiting for the next incoming event if your input already publishes at the interval you expect, enter 0 to disable the timer parameters parameter details window size the window (in seconds) over which the gaussian filter calculates the mean and standard deviation timer interval sets a timer (in milliseconds) that continuously publishes the output when no event triggers the filter enter 0 to disable the timer pass through value determines whether the processor's output is the filtered value or the original unchanged input value related topics use the gaussian filter function docid\ xbbag37w xrnnn7t9x6zq