Adaptive Symbol Compression Using Dynamic Conversion Tables
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Solution Overview
Problem
Existing data compression/decompression systems face challenges in creating and applying conversion rules that can be applied in common to data streams with different symbol appearance tendencies, especially when each data compressor and decompressor is provided by hardware with limited storage capacity for pre-conversion and post-conversion symbol correspondences.
Innovation Solution
A data compression/decompression system processes data strings in units of symbols, dynamically creating and updating a conversion table based on symbol frequencies, allowing for real-time adaptation of compression and decompression rules to match the data stream's tendency, without the need for a shared lookup table.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conversion table is shared in advance between transmitter and receiver, then compression efficiency can be improved, but the system cannot adapt to data streams with different symbol appearance tendencies and hardware storage capacity is limited
Solution Approach 1:
The patent applies dynamics by making the conversion table changeable during operation. The transmitter and receiver both dynamically update their conversion tables based on the frequency of symbol appearances in the data stream. This allows the system to adapt to different data streams while maintaining compression efficiency, resolving the contradiction between using a fixed shared table and adapting to varying data characteristics.
Solution Approach 2:
The patent changes the parameters of the conversion table based on symbol frequency statistics. By monitoring how often symbols appear and adjusting the conversion rules accordingly, the system optimizes compression for the current data stream while maintaining the ability to handle different types of data. This parameter adaptation resolves the contradiction between efficiency and versatility.
2Device complexity
If conversion rules are fixed in advance, then hardware implementation is simpler, but the system cannot optimize for different data stream patterns
Solution Approach 1:
The patent performs preliminary actions by initializing conversion tables with default rules before processing data streams. This provides a simple starting point for hardware implementation while allowing subsequent dynamic updates to optimize for specific data patterns. The preliminary setup maintains simplicity while enabling later adaptation.
Solution Approach 2:
The system uses feedback by monitoring symbol frequency during data stream processing and using this information to update the conversion table. This feedback mechanism allows the hardware to automatically optimize compression efficiency for different data patterns without complex manual configuration, resolving the contradiction between simplicity and adaptability.
3Speed
If data is transmitted without compression, then transmission speed is faster per unit time, but the amount of data transmitted increases
Solution Approach 1:
The patent changes the parameter of data representation by converting frequent symbol sequences into shorter coded representations. This parameter transformation reduces the volume of transmitted data while maintaining transmission speed, as the same amount of information is conveyed in fewer bits.
Data Source
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AI summary
In a data compression method, a data string is compressed in units of symbols, each of the symbols being data having a fixed length. Then, a conversion table in which an entry indicating a correspondence between two or more pre-conversion symbols and one post-conversion symbol is registered is searched, and if it is determined that two or more consecutive symbols in the data string are not registered as two or more pre-conversion symbols, an entry in which the two or more consecutive symbols are registered as two or more pre-conversion symbols is registered in the conversion table, and the two or more consecutive symbols are output without conversion, and if two or more consecutive symbols in the data string are registered as two or more pre-conversion symbols in an entry in the conversion table, the two or more consecutive symbols are converted into one post-conversion symbol, the one post-conversion symbol being in correspondence with the two or more consecutive symbols in the entry.