ANBD Data Encoding With Configurable Base for Fast Error Detection
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Solution Overview
Problem
Current ANBD coding for safety-related applications is complex and inefficient, particularly for floating-point arithmetic, leading to significantly longer computing times and inaccuracies due to its reliance on integer arithmetic, which is not flexible enough for floating-point operations.
Innovation Solution
A method that normalizes a functional variable to a base, allowing it to be represented as an integer multiple of that base, enabling operations using integer arithmetic while maintaining flexibility and reducing maximum error, by converting floating-point numbers into integer values and performing calculations with optimized bases to minimize rounding errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If floating-point arithmetic is implemented using ANBD coding, then error detection capability is improved, but computing time increases by orders of magnitude
Solution Approach 1:
The patent changes the parameter of numerical representation from floating-point to fixed-point with a configurable base. By representing numbers as integers multiplied by a base (e.g., base 1000 or base 10), the system maintains error detection through ANBD coding while avoiding the computational complexity of floating-point operations. This parameter change allows using simpler integer arithmetic while preserving the essential error detection capabilities.
Solution Approach 2:
The patent introduces dynamic base selection where the base can be configured according to specific application requirements. The base parameter can be adjusted to optimize between precision and computational efficiency for different use cases. This dynamic approach allows the system to adapt the numerical representation to match the specific needs of each application, balancing error detection capability with computing performance.
2Productivity
If fixed-point arithmetic is used instead of floating-point, then computing time is reduced, but accuracy is insufficient for complex processing
Solution Approach 1:
The patent changes the parameter of numerical precision by introducing a configurable base parameter. Instead of using standard fixed-point with base 2, the system allows bases like 1000 or 10, which provide better human-readable precision and more appropriate granularity for many engineering applications. This parameter change enables fixed-point arithmetic to achieve accuracy levels previously only available through floating-point operations.
Solution Approach 2:
The patent adds a new dimension to fixed-point arithmetic by introducing the base parameter as an additional degree of freedom. Traditional fixed-point is constrained to base 2, but this invention operates in a broader space of possible bases, allowing optimization of precision for specific applications. This dimensional extension transforms fixed-point from a limited approach into a flexible precision mechanism.
3Reliability
If ANBD coding is applied to ensure data protection, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent simplifies the ANBD coding implementation by changing the parameter of numerical representation to fixed-point with a configurable base. This parameter change reduces the complexity of arithmetic operations while maintaining the core error detection functionality. The simplified arithmetic operations reduce the overall device complexity while preserving data protection capabilities.
Data Source
Figure 1
AI summary
The invention relates to a method for protecting the data in a data storage device from undetected changes, wherein a functional variable x is encoded to a coded variable xc by means of a value valuex, an input constant A, an input signature Bx and a timestamp D according to the formula xc:=valuex*A+Bx+D, wherein to form the integer value valuex from the functional variable x, the latter is normalized with respect to a basis basisx.