Kalman Filtering

With kalman filtering systems, we provide beteter systems are able to adapted themselves to existing sensors without calibration or sensor degradation overtime.

By using a series of measurements observer over time, containing random variations and other inaccuracies, the kalman filter produces estimates of unknown variables that tend to be more precise, comparing to other algorithm that based on a single measurement alone.

The advantage of kalman filtering is it actually makes the system smarter. Our design help our clients develop systems that do not need calibration over time, and thus reduce monitoring costs.

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Parallel Computing
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