Real Number Error Correction for Biometric Data Processing
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Solution Overview
Problem
Existing technologies face challenges in performing error correction on real number data, particularly in the context of biometric authentication, where existing fuzzy extraction technologies are limited to binary data and struggle with real number data.
Innovation Solution
The development of an electronic apparatus and method that enables error correction on real number data by generating a codeword and a helper matrix, allowing for direct processing of real number data without the need for conversion to binary data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing fuzzy extraction technology is used, then binary data can be processed, but real number data cannot be processed
Solution Approach 1:
The patent changes the fundamental parameter of data representation from binary to real number domain. By formulating error correction codes in the real number field rather than binary field, the system achieves versatility across different data types while maintaining error correction reliability through mathematical transformations that preserve error detection and correction capabilities in the continuous domain.
Solution Approach 2:
The invention creates a universal error correction framework that can handle both binary and real number data. By developing a generalized error correction code that operates in the real number domain, the system achieves multi-functionality where the same theoretical framework applies to different data types, eliminating the limitation of binary-only processing while maintaining robust error correction.
2Reliability
If data conversion to binary is performed, then existing error correction can be applied, but processing accuracy decreases
Solution Approach 1:
Instead of converting real number data to binary for error correction, the patent inverts the approach by developing error correction codes that natively operate in the real number domain. This eliminates the accuracy loss from conversion while maintaining error correction capability, as the correction algorithms work directly with continuous values rather than discretized binary representations.
Solution Approach 2:
The patent replaces the mechanical binary conversion process with a mathematical substitution approach. By using real number field arithmetic and continuous error correction algorithms instead of binary field operations, the system maintains measurement precision while achieving error correction through mathematical transformations that preserve the continuous nature of the data.
3Reliability
If binary conversion is performed, then error correction is possible, but processing time increases
Solution Approach 1:
The patent performs preliminary formulation of error correction codes in the real number domain, eliminating the need for subsequent binary conversion steps. By pre-establishing the error correction framework to work natively with real number data, the system removes unnecessary conversion overhead and achieves faster processing while maintaining error correction capability throughout the data pipeline.
Data Source
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AI summary
A data processing method is disclosed. The data processing method comprises the steps of: selecting, as a codeword, one from among vectors, which are composed of multiple elements and have a predetermined size, generating a helper matrix by using the selected codeword and real number data; and outputting the helper matrix.