Polynomial Temperature Compensation for Low Power Oceanographic Telemetry Loggers
Polynomial temperature compensation executes low-power integer matrix math in subsea loggers to eliminate sensor thermal drift while preserving battery life.
Minimax Error
Meaning
Mathematical objectives minimize the maximum absolute difference between a theoretical function and its simplified numerical representation. A minimax error approach is used in the design of digital filters and approximation algorithms to ensure that the worst case performance is as good as possible. This method distributes the deviation across the entire range of the function rather than allowing large spikes at specific points.
It creates a balanced ripple effect across the approximation. The application is common in signal processing where predictable precision is necessary for reliable data conversion.
Approximation Bound
Constraints on the hardware often require the use of low order polynomials to represent complex curves. The goal of the minimax error calculation is to find coefficients that keep the result within a tight envelope. Engineers select this strategy when the cost of a large error at any single point exceeds the benefit of a smaller average error.
Numerical Precision
Performance depends on the bit depth and the computational power available in the system. While other methods might minimize the total squared error, the minimax error focus provides a guaranteed limit on the deviation. This guarantee is essential for safety critical systems where every output must stay within defined tolerances.
Tolerance Limit
Stability in the system response is achieved by smoothing out the approximation. Once the minimax error is established, the designer can predict the maximum noise level introduced by the algorithm. This predictability allows for better integration with other software components.