Nonlinear Post-Processor for Transition Jitter Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current detectors designed to combat signal-dependent noise, such as transition jitter, are complex and perform poorly when noise variance is large, limiting their effectiveness in high-variance environments.
Innovation Solution
A nonlinear post-processor architecture that computes and minimizes transition jitter and white noise costs to select the final decision from preliminary detector outputs, reducing decision errors and improving detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current detectors with complicated correction schemes are used to combat signal-dependent noise, then detection accuracy improves, but device complexity increases
Solution Approach 1:
The detection system is divided into two functional segments: a sub-optimal detector that provides preliminary decisions, and a nonlinear post-processor that corrects decision errors. This segmentation allows each component to be optimized independently, reducing overall complexity while maintaining detection accuracy.
Solution Approach 2:
The nonlinear post-processor acts as an intermediary between the sub-optimal detector and the final decision output. It receives preliminary decisions, computes cost metrics considering signal-dependent noise, and selects the optimal decision, thereby improving accuracy without requiring the detector itself to be complex.
2Device complexity
If first-order Taylor approximation is used for noise process, then computational complexity is reduced, but measurement precision deteriorates when noise variance is large
Solution Approach 1:
The system dynamically changes the noise variance parameter to adapt the detection strategy. When noise variance is small, simpler methods suffice; when noise variance is large, the nonlinear post-processor employs more sophisticated cost metric computations, optimizing the balance between complexity and precision based on actual noise conditions.
Data Source
AI summary
A non-linear post-processor for estimating at least one source of signal-dependent noise is disclosed. The post processor may receive a set of preliminary decisions from a sub-optimal detector along with the sampled data signal. The post-processor may then compute the transition jitter and white noise associated with each preliminary decision in the set and assign a cost metric to each decision based on the total signal noise. The post-processor may output the decision with the lowest cost metric as the final decision of the detector.