Dynamic Symbol Alphabet Binding for Header-Efficient Data Compression
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Solution Overview
Problem
Existing data compression algorithms face inefficiencies due to the fixed and unchanging nature of the alphabet used, which can lead to suboptimal compression ratios and increased storage size due to the inclusion of unnecessary symbols and larger headers.
Innovation Solution
The dynamic selection of alphabets based on the digital data and compression parameters allows for the exclusion of unnecessary symbols and the use of shorthand forms, enabling more efficient compression by representing sequences of bits with fewer bits and adjusting symbol hierarchies within the alphabet.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a larger alphabet is used to replace greater quantities of bits with a single symbol, then compression efficiency is improved, but header size increases thereby increasing the size of compressed digital data
Solution Approach 1:
The patent implements dynamic alphabet selection where the alphabet is not fixed but is chosen from multiple candidate alphabets based on the specific characteristics of the digital data being compressed. This allows the system to adapt the alphabet size and composition to match the data patterns, achieving high compression efficiency without consistently using large alphabets that would inflate header sizes. The dynamic binding of symbol alphabets enables the system to select the most appropriate alphabet for each data set, optimizing the trade-off between compression ratio and header overhead.
Solution Approach 2:
The patent changes the parameter of alphabet size and composition based on the input data characteristics. By selecting from multiple alphabets with different sizes and symbol sets, the system can adjust the alphabet parameters to match the data being compressed. This parameter adaptation allows the system to use smaller alphabets for data types that don't benefit from large symbol sets, thereby reducing header size while maintaining compression efficiency for appropriate data types.
2Ease of manufacture
If a single predefined alphabet is used, then implementation is simplified, but compression ratio is reduced due to inability to exclude unnecessary symbols
Solution Approach 1:
The system transitions from a static, single predefined alphabet to a dynamic multi-alphabet selection mechanism. Multiple candidate alphabets are prepared in advance, and the system dynamically selects the most appropriate one based on data characteristics. This maintains implementation simplicity through pre-defined candidate alphabets while achieving better compression ratios by selecting the optimal alphabet for each data set, excluding unnecessary symbols that would otherwise be included in a universal alphabet.
Solution Approach 2:
Different alphabets are designed with different symbol sets optimized for different data types or patterns. The system selects the alphabet that best matches the local characteristics of the input data, applying the principle of local quality by tailoring the symbol set to the specific data being compressed. This allows each alphabet to be optimized for its intended use case, achieving better compression ratios without requiring a single overly complex universal alphabet.
3Productivity
If multiple different alphabets are selected for different portions of digital data, then compression efficiency is improved, but device complexity increases due to multiple headers and alphabet information management
Solution Approach 1:
The patent divides the digital data into multiple portions or segments, each of which can be compressed using a different selected alphabet. This segmentation allows the system to apply the most appropriate alphabet to each data portion, improving overall compression efficiency. The complexity of managing multiple alphabets is reduced by processing data in manageable segments rather than requiring complex global alphabet management across the entire data set.
Solution Approach 2:
Multiple candidate alphabets are prepared and characterized in advance before the compression process begins. This preliminary action allows the system to quickly select the appropriate alphabet based on data characteristics without performing complex analysis during compression. The pre-prepared alphabets and their associated metadata are stored and readily available, reducing the complexity of alphabet management during the actual compression operation.
Data Source
AI summary
The generation of symbol-encoded data from digital data, as part of the compression of the digital data into a compressed digital data, can be performed with reference to multiple alternative alphabets. A selection of a specific alphabet is made based on the digital data being compressed, the compression parameters, or combinations thereof. Information indicative of the selected alphabet is encoded into one or more headers of the resulting compressed digital data. A single alphabet can be selected for all of a set of digital data being compressed, or multiple different alphabets can be selected, with different ones of the multiple different alphabets being utilized to compress different portions of the digital data. Additionally, rather than explicitly specifying a specific selected alphabet, the header information can comprise information from which a same alphabet can be independently selected heuristically by both the compressor and the corresponding decompressor.