Kolmogorov Complexity Estimation via Phrase Partitioning
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Solution Overview
Problem
The estimation of Kolmogorov Complexity for a finite string is inefficient due to the time and resource-intensive nature of the Lempel/Ziv 78 compression algorithm, which requires encoding, compression, and inverse compression ratio calculations.
Innovation Solution
A data transmission system that estimates Kolmogorov Complexity by partitioning the string into unique phrases, determining the number of phrases, and using the formula C≡N^2*L to calculate a normalized complexity estimate, allowing or rejecting data transmission based on whether this estimate falls within a predetermined complexity band.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the LZ78 compression algorithm is used to estimate Kolmogorov Complexity, then the estimation accuracy is improved, but the computational time and resource consumption increase significantly
Solution Approach 1:
The patent extracts only the essential component needed for complexity estimation from the full LZ78 algorithm. Instead of implementing the complete compression process with encoding and decoding, it extracts solely the partitioning mechanism that divides the string into phrases, discarding the time-consuming compression and decompression steps while retaining the core capability to measure complexity through phrase count.
Solution Approach 2:
The patent performs only the necessary portion of the LZ78 algorithm (partitioning) without completing the full compression process. By performing partial action - just the partitioning step rather than the entire encode-compress-decode cycle - the system achieves sufficient complexity estimation accuracy without the excessive time and resource consumption of the complete algorithm.
2Measurement precision
If the LZ78 compression algorithm is used to estimate Kolmogorov Complexity, then the estimation accuracy is improved, but the resource consumption increases
Solution Approach 1:
The patent extracts only the essential component needed for complexity estimation from the full LZ78 algorithm. Instead of implementing the complete compression process with encoding and decoding, it extracts solely the partitioning mechanism that divides the string into phrases, discarding the time-consuming compression and decompression steps while retaining the core capability to measure complexity through phrase count.
Solution Approach 2:
The patent performs only the necessary portion of the LZ78 algorithm (partitioning) without completing the full compression process. By performing partial action - just the partitioning step rather than the entire encode-compress-decode cycle - the system achieves sufficient complexity estimation accuracy without the excessive time and resource consumption of the complete algorithm.
3Measurement precision
If the complete LZ78 compression process is performed, then the complexity estimation is more accurate, but the processing efficiency decreases
Solution Approach 1:
The patent extracts only the essential component needed for complexity estimation from the full LZ78 algorithm. Instead of implementing the complete compression process with encoding and decoding, it extracts solely the partitioning mechanism that divides the string into phrases, discarding the time-consuming compression and decompression steps while retaining the core capability to measure complexity through phrase count.
Solution Approach 2:
The patent performs only the necessary portion of the LZ78 algorithm (partitioning) without completing the full compression process. By performing partial action - just the partitioning step rather than the entire encode-compress-decode cycle - the system achieves sufficient complexity estimation accuracy without the excessive time and resource consumption of the complete algorithm.
Data Source
AI summary
A system, method and program storage device tangibly embodying a program of instructions for determining whether to allow transmission of data from a source destined for a destination over a network, comprising: acquiring a string of a predetermined length in bits (L) from the data; partitioning the acquired string into a partition of phrases, each of the phrases in the partition being unique and having one or more bits; determining a number of phrases (N) in the partition; estimating a normalized complexity (C) for the Kolmogorov Complexity in the acquired string viaC≡N2L;and evaluating whether to allow transmission of the data based on a comparison of whether the normalized complexity estimate (C) is within a predetermined normal complexity estimate band.


