Segment-Based Data Averaging Circuit for Storage Noise Reduction
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Solution Overview
Problem
Noise in data retrieval from storage media often prevents read channel circuits from accurately recovering the originally written data, leading to failed read processes.
Innovation Solution
The implementation of data processing circuits that include a read circuit and a combining circuit, which perform segment-based averaging by combining multiple instances of user data sets to create aggregate data sets, using data detection and decoding algorithms to enhance noise reduction and data recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple reads are performed to recover data from storage medium, then data recovery reliability is improved, but read time and system productivity deteriorate
Solution Approach 1:
The system performs preliminary segment-based averaging on newly read data before attempting full data recovery. By pre-processing and combining segments from multiple reads in advance, the system prepares averaged data that can be directly used for recovery, reducing the need for repeated full read operations and thereby decreasing total read time while maintaining high reliability.
Solution Approach 2:
The patent divides user data into multiple segments and processes each segment independently through averaging operations. This segmentation allows parallel processing of different data portions, enabling the system to efficiently combine information from multiple reads without processing the entire data set sequentially, thus reducing overall processing time while improving recovery reliability.
2Reliability
If multiple reads are performed to recover data from storage medium, then data recovery reliability is improved, but device complexity increases
Solution Approach 1:
The patent divides user data into multiple segments and processes each segment independently through averaging operations. This segmentation allows parallel processing of different data portions, enabling the system to efficiently combine information from multiple reads without processing the entire data set sequentially, thus reducing overall processing time while improving recovery reliability.
Solution Approach 2:
The combining circuit is designed to universally handle multiple data instances and segments through a standardized averaging process. This multi-functional approach allows the same circuit architecture to process different data sets and segment combinations, reducing the need for specialized circuits for each specific recovery scenario and thereby managing device complexity.
3Measurement precision
If segment-based averaging is performed to reduce noise, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent divides user data into multiple segments and processes each segment independently through averaging operations. This segmentation allows parallel processing of different data portions, enabling the system to efficiently combine information from multiple reads without processing the entire data set sequentially, thus reducing overall processing time while improving recovery reliability.
Solution Approach 2:
The system applies different averaging coefficients to different segments based on their individual quality characteristics. By analyzing each segment's noise level and data quality, the circuit assigns appropriate weights during the averaging process, thereby optimizing noise reduction precision for each local segment while managing overall system complexity through localized processing.
Data Source
AI summary
Various embodiments of the present invention provide systems and methods for data processing. As an example, a data processing circuit is disclosed that includes a read circuit and a combining circuit. The read circuit is operable to provide a first instance of a user data set, a second instance of the user data set, and a third instance of the user data set. The combining circuit is operable to: combine at least a first segment of the first instance of the user data set with a first segment of the second instance of the user data set to yield a first combined data segment; provide a second combined data set that includes a combination of one or more second segments from the second instance of the user data set and the third instance of the user data set; and provide an aggregate data set including at least the first combined data set and the second combined data set. The second combined data set does not incorporate a second segment of the first instance of the user data set.