Digital Delay Line Architecture for Similarity-Based Data Comparison
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Solution Overview
Problem
Conventional computers are limited in comparing data samples due to their reliance on ordinal numbers, which only provide information about sequence order, failing to determine similarity between data samples unless there is an exact match, leading to complex signal processing requirements that reduce system speed and performance.
Innovation Solution
The implementation of a correlithm object processing system using categorical numbers and correlithm objects, which allows for non-binary comparisons and quantification of similarity between data samples, enabling efficient comparison of data samples regardless of their type or format through the use of sensor, node, and actor tables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional computers use ordinal binary integers to represent and manipulate data samples, then they can perform operations such as counting, sorting, indexing, and mathematical calculations, but they are unable to determine similarity between different data samples without exact matches
Solution Approach 1:
The patent transforms the numerical representation system from ordinal binary integers to a similarity-based encoding system. Instead of relying on numerical order, the system encodes data samples in a format that inherently represents similarity relationships, allowing direct comparison operations without complex signal processing.
Solution Approach 2:
The patent replaces the mechanical/mathematical signal processing techniques with a fundamentally different approach using similarity-based numerical representation. This substitution eliminates the need for complex comparison algorithms by encoding similarity information directly in the numerical representation.
2Reliability
If conventional computers rely on complex signal processing techniques to determine similarity between data samples, then they can identify matches, but the processes consume significant processing power which reduces system speed and performance
Solution Approach 1:
The patent performs preliminary encoding of data samples into similarity-based representations during data ingestion or preprocessing. This preliminary action embeds similarity information directly into the numerical representation, so that subsequent comparison operations are simple and fast, eliminating the need for complex real-time signal processing.
3Loss of information
If conventional computers use ordinal numbers to represent data samples, then they can store and manipulate information, but the numerical values do not provide information about how similar or dissimilar different data samples are
Solution Approach 1:
The patent changes the fundamental parameter of numerical representation from ordinal value to similarity encoding. Each data sample is represented by a number that reflects its similarity relationships with other samples, preserving similarity information that is then easily accessible through simple numerical operations.
Data Source
AI summary
A device that includes a first correlithm object delay device, a second correlithm object delay device, and a third correlithm object delay device. The a first correlithm object delay device is operable to receive a first correlithm object at a first time, store the first correlithm object, and output the first correlithm object at a second time later than the first time. The second correlithm object delay device is operable to receive the first correlithm object at a third time later than the second time, store the first correlithm object, and output the first correlithm object at a fourth time later than the third time. The third correlithm object delay device is operable to receive the first correlithm object at a fifth time later than the fourth time, store the first correlithm object, and output the first correlithm object at a sixth time later than the fifth time.