Correlithm Object Processing for Data Similarity Detection

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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, leading to complex signal processing challenges and reduced performance in applications like facial recognition and fraud detection.

Innovation Solution

The implementation of a correlithm object processing system that uses categorical numbers and correlithm objects to represent data samples, enabling non-binary comparisons and quantifying similarity between data samples, regardless of their type or format, through the use of sensor, node, and actor tables.

Engineering Contradictions & Design Principles

VSEngineering 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 cannot determine similarity between different data samples unless there is an exact match

Engineering Contradiction:

Improvedata sample comparison accuracyVSAvoidsignal processing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent transforms the numerical representation system from ordinal binary integers to a similarity-based numerical system. Instead of relying on exact numerical matches, the system uses numerical values that encode similarity relationships, allowing computers to determine similarity without complex signal processing while maintaining comparison accuracy

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces complex mechanical signal processing techniques with a simplified numerical comparison system. By encoding similarity information directly in the numerical representation of data samples, the system eliminates the need for elaborate signal processing algorithms while achieving reliable similarity determination

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If conventional computers rely on complex signal processing techniques to determine similarity between data samples, then they can achieve accurate comparison, but processing power is consumed which reduces system speed and performance

Engineering Contradiction:

Improvedata sample similarity determination accuracyVSAvoidsystem processing speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent performs preliminary encoding of similarity information during data representation. By pre-encoding similarity relationships in the numerical values themselves, the system eliminates the need for computationally intensive signal processing during comparison operations, thereby maintaining accuracy while significantly improving processing speed

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent extracts similarity information from complex signal processing operations and embeds it directly into the numerical representation of data samples. This extraction allows the system to determine similarity through simple numerical comparison rather than consuming processing power on elaborate signal analysis

Inventive Principle:

Principle #2Taking out (Extraction)

3Quantity of substance

If conventional computers use ordinal numbers to represent data samples, then they can store and manipulate information efficiently, but they lose information about relationships between data samples such as similarity

Engineering Contradiction:

Improveinformation storage capacityVSAvoidsimilarity relationship information

Core Design Contradiction:

Quantity of substanceVSLoss of information

Solution Approach 1:

The patent merges multiple types of information (identity and similarity relationships) into a single numerical representation system. The numerical values simultaneously encode both the unique identity of each data sample and its similarity relationships with other samples, preserving relationship information while maintaining efficient storage and manipulation capabilities

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS10990649B2Computer architecture for emulating a string correlithm object velocity detector in a correlithm object processing system

Publication Date: 2021.04.27 BANK OF AMERICA CORP

AI summary

A device configured to emulate a string correlithm object velocity detector includes a memory that stores a first string correlithm object comprising a plurality of sub-string correlithm objects. The device further includes a sensor coupled to the memory and configured to determine a time between performing data processing associated with the plurality of sub-string correlithm objects, and represent those times as correlithm objects.