Universal Codebook Encoding for Unseen Data Compaction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage technologies face challenges in efficiently handling rapidly increasing data demands due to limited storage capacity and bandwidth constraints, particularly with the rise of multimedia data, and existing entropy encoding methods fail to effectively compact previously unseen data.
Innovation Solution
A system and method utilizing mismatch probability estimation to improve entropy encoding by calculating the frequency of occurrence of data sourceblocks and inserting mismatch codewords into codebooks, enabling efficient handling of unseen data through a universal codebook and secondary encoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing entropy encoding methods are used, then data compaction is achieved for previously-seen data, but previously-unseen data cannot be efficiently encoded
Solution Approach 1:
The system performs preliminary actions by pre-calculating mismatch probabilities during the training phase and pre-inserting mismatch codewords into the codebook before actual encoding occurs. This allows the encoder to handle previously-unseen data efficiently during runtime without performing complex calculations on-the-fly.
Solution Approach 2:
Mismatch codewords act as intermediaries between the codebook and previously-unseen data. When a sourceblock does not match any entry in the codebook, the system uses the pre-inserted mismatch codeword to represent it, enabling efficient encoding of unseen data without requiring exact matches.
2Measurement precision
If codebook size is increased to accommodate more sourceblocks, then encoding accuracy improves, but storage and bandwidth requirements increase
Solution Approach 1:
The system changes the parameter of codebook entries by inserting special mismatch codewords with specific probability values. These mismatch codewords have associated probability estimates that allow the encoder to efficiently represent unseen data without expanding the codebook to include every possible sourceblock.
Solution Approach 2:
Instead of copying every possible sourceblock into the codebook, the system creates a simplified representation using mismatch codewords that copy the essential function of representing unseen data. This allows accurate encoding without the storage overhead of a complete codebook.
3Adaptability or versatility
If mismatch probability estimation is performed during encoding, then handling of unseen data improves, but computational complexity increases
Solution Approach 1:
The system performs the computationally intensive mismatch probability estimation during the training phase rather than during actual encoding. The trained mismatch probabilities are stored and reused during encoding, significantly reducing the computational complexity of the encoding process while maintaining the ability to handle unseen data.
Solution Approach 2:
The system uses pre-computed mismatch probabilities from training data to serve itself during encoding operations. This self-service approach allows the encoder to efficiently handle unseen data using stored probability information without requiring complex real-time calculations.
Data Source
AI summary
Codebook data compaction using a universal codebook and mismatch probability estimations to improve entropy encoding methods. Training data sets are analyzed to determine the frequency of occurrence of each sourceblock in the training data sets. A mismatch probability estimate is calculated comprising an estimated frequency at which any given data sourceblock received during encoding will not have a codeword in the codebook. Entropy encoding is used to generate codebooks comprising codewords for data sourceblocks based on the frequency of occurrence of each sourceblock. A “mismatch codeword” is inserted into the codebook based on the mismatch probability estimate to represent those cases when a block of data to be encoded does not have a codeword in the codebook.