Multi-Dimensional Signal Equalization for Low-SNR Data Recovery
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Solution Overview
Problem
Existing data processing systems face challenges in recovering originally written data sets due to low signal-to-noise ratios, often requiring re-sensing and reprocessing, which may not result in successful data recovery.
Innovation Solution
The implementation of multi-dimensional equalization systems and methods that utilize multiple equalizer circuits to equalize data sets, aggregate outputs, and store them in update buffers, improving signal quality through digital finite impulse response circuits and data processing algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If re-sensing and reprocessing are performed multiple times to recover data, then data recovery reliability may improve, but processing time and system complexity increase
Solution Approach 1:
The patent applies preliminary action by performing equalization processing on previously sensed data before attempting recovery. The equalizer circuits pre-process the low signal-to-noise ratio data to improve its quality, making subsequent recovery attempts more successful and reducing the need for repeated re-sensing operations.
Solution Approach 2:
The patent introduces equalizer circuits as intermediary components between the sensed data and the recovery process. These equalizers act as mediators that enhance the quality of low signal-to-noise ratio data through equalization processing, enabling more reliable recovery without requiring multiple re-sensing cycles.
2Reliability
If advanced equalization processing is applied to low signal-to-noise ratio data, then data recovery success rate improves, but device complexity increases
Solution Approach 1:
The patent segments the equalization processing into multiple independent equalizer circuits, each handling specific aspects of the equalization task. This segmentation allows the complex equalization function to be divided into manageable components that can be implemented and controlled separately, reducing overall system complexity while maintaining high recovery success rates.
Solution Approach 2:
The patent applies multi-dimensional equalization by processing data across multiple dimensions or perspectives simultaneously using different equalizer circuits. This approach enhances recovery success by considering multiple factors of signal degradation independently and combining their effects, achieving superior results without requiring a single overly complex processing unit.
3Measurement precision
If multiple equalizer circuits are used to process data sets, then signal-to-noise ratio improvement increases, but circuit complexity and resource requirements increase
Solution Approach 1:
The patent merges the outputs of multiple equalizer circuits through addition to produce a combined result. By summing the equalized outputs from different circuits, the system achieves improved signal-to-noise ratio through constructive combination of processed signals, leveraging the strengths of each equalizer while sharing common infrastructure.
Solution Approach 2:
The patent designs equalizer circuits with universal functionality that can process different data sets and adapt to various signal conditions. This multi-functionality allows the same circuit architecture to be reused across multiple processing tasks, reducing overall device complexity despite employing multiple equalizer circuits for different data sets.
Data Source
AI summary
Embodiments are related to systems and methods for data processing, and more particularly to systems and methods for equalizing a data signal.