Correlithm Object Processing System for Hamming Distance Measurement
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Solution Overview
Problem
Conventional computers are limited in comparing data samples for similarity due to their reliance on ordinal numbers, which only provide information about sequence order, leading to complex signal processing requirements and reduced speed and performance in applications like face recognition and fraud detection.
Innovation Solution
The implementation of a correlithm object processing system that uses categorical numbers and correlithm objects to enable non-binary comparisons and quantify similarity between data samples, allowing for direct comparison of data samples regardless of their type or format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional computers use ordinal binary integers to represent and manipulate data samples, then they can perform operations like counting, sorting, and indexing, but they cannot determine similarity between different data samples without complex signal processing techniques
Solution Approach 1:
The patent transforms the representation parameter of data samples from ordinal binary integers to correlithm objects in a high-dimensional space. This parameter change enables direct similarity measurement through geometric distance calculations, eliminating the need for complex signal processing while providing precise similarity determination between different data samples
Solution Approach 2:
The patent maps data samples into a high-dimensional space using correlithm objects, transitioning from one-dimensional ordinal representation to multi-dimensional geometric representation. This dimensional transformation allows similarity to be measured directly through spatial distance metrics, resolving the contradiction between measurement precision and processing complexity
2Measurement precision
If conventional computers rely on complex signal processing techniques to compare data samples for similarity, then they can determine matching or similarity, but the processing power consumption increases and system speed decreases
Solution Approach 1:
The patent replaces complex mechanical signal processing operations with straightforward geometric distance calculations in high-dimensional space. The correlithm object representation allows similarity comparison to be performed through simple coordinate-based distance metrics, dramatically improving processing speed while maintaining comparison accuracy
Solution Approach 2:
By changing the representation parameter from ordinal numbers to correlithm objects with geometric properties, the patent enables direct distance-based similarity measurement. This parameter transformation eliminates computationally intensive signal processing steps, thereby increasing processing speed without sacrificing comparison precision
3Loss of information
If conventional computers use ordinal numbers to represent data samples, then they can store and manipulate information efficiently, but they lack the ability to provide information about relationships such as similarity between data samples
Solution Approach 1:
The correlithm object representation serves multiple functions simultaneously: it enables efficient storage and manipulation of data samples while also encoding relationship information such as similarity through geometric properties. This universal representation format eliminates the need for separate processing to determine relationships, as the information is inherently embedded in the geometric structure
Solution Approach 2:
By representing data samples as correlithm objects in high-dimensional space, the patent adds geometric dimensions that inherently encode relationship information. The spatial relationships between correlithm objects directly represent similarity and other relationships, providing adaptability for various data analysis tasks while maintaining efficient storage and manipulation capabilities
Data Source
AI summary
A system that includes an XOR logic gate, a shift register, and a counter. The XOR logic gate is configured to receive a pair of correlithm objects, to perform an XOR operation on the pair of correlithm objects to generate a binary string, and transfer the binary string to the shift register. Each correlithm object is a point in an n-dimensional space represented by a binary string. The shift register is configured to bitwise shift the binary string to the counter. The counter is configured to sequentially receive each bit of the binary string and determine whether a received bit has a logical high value. The counter is configured to increment a count value in response to determining the received bit has a logical high value and output the count value which indicates the distance between the pair of correlithm objects.