NPML Filter Calibration Using Adaptive Coefficient Updates
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Solution Overview
Problem
Existing data processing systems face inaccuracies in noise predictive filtering, leading to ineffective data transfer due to noise in various scenarios.
Innovation Solution
The implementation of adaptive parameter modification systems that include a data detector circuit with noise predictive maximum likelihood (NPML) filtering, a data decoder circuit, and a filter calibration circuit, which updates filter coefficients using converged outputs and inputs to improve data processing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If noise predictive filtering is used to deal with noise in data transfer, then data transfer effectiveness is improved, but measurement precision deteriorates due to inaccurate results in various noise scenarios
Solution Approach 1:
The patent implements dynamic adaptation of filtering parameters by continuously monitoring signal characteristics and adjusting filter coefficients in real-time. The system transitions from static filtering to adaptive filtering where parameters change based on current noise conditions, resolving the contradiction between maintaining effectiveness across varying noise scenarios and preserving measurement precision.
Solution Approach 2:
The patent changes the parameters of the noise predictive filter based on detected noise characteristics. By modifying filter coefficients, prediction windows, and other parameters dynamically according to the actual noise environment, the system maintains both transfer effectiveness and filtering accuracy across different noise scenarios.
2Measurement precision
If adaptive parameter modification is implemented to improve filtering accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the filtering system automatically monitors its own performance, detects degradation or noise changes, and adjusts its parameters without external intervention. This self-adaptive capability improves filtering accuracy while avoiding the need for complex external control systems.
Solution Approach 2:
The patent incorporates feedback loops where the output of the filtering process is monitored and fed back to adjust filter parameters. This closed-loop control enables automatic adaptation to improve accuracy while using relatively simple feedback mechanisms rather than complex control systems.
Data Source
AI summary
The present invention is related to systems and methods for adaptive parameter modification in a data processing system. As one example, a system is disclosed that includes a filter calibration circuit that is operable to calculate an updated coefficient for a filter circuit using a data set pair including a converged output and a corresponding data set.