Shared Symbol Co-Compression for Adjustable Data Accuracy

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Solution Overview

Problem

Existing data compression techniques fail to dynamically adjust the accuracy of co-compressed data values, leading to inefficiencies in representing multiple data values, especially when one value is more important than the other, as they require fixed bit allocation for all data values.

Innovation Solution

A method involving the generation of a shared symbol sequence where the most significant symbol of one data value is also the most significant symbol of the other, allowing for different reading directions to extract the compressed representations, enabling dynamic adjustment of accuracy by sharing symbols between the two data values.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a fixed number of bits is allocated for each data value in co-compression, then the compression structure remains simple and uniform, but the accuracy of individual data values cannot be adjusted dynamically

Engineering Contradiction:

Improveaccuracy of data value representationVSAvoidcomplexity of compression structure

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the symbol sequence into different portions that can be allocated to different data values. A first portion of the symbol sequence represents the first data value, while a second portion represents the second data value. This segmentation allows flexible allocation of symbols to achieve desired accuracy for each data value without requiring a completely complex compression structure.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent implements dynamic allocation of symbols from the symbol sequence to different data values based on their relative importance. The system can adjust the number of symbols allocated to each data value dynamically, allowing higher accuracy for more important data values while maintaining lower accuracy for less important ones, all within a unified compression framework.

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If lattice vector quantization is used to adjust accuracy between data values, then dynamic accuracy adjustment is achieved, but decompression complexity increases due to matrix multiplication

Engineering Contradiction:

Improveaccuracy of data value representationVSAvoidsimplicity of decompression process

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent replaces the complex matrix multiplication operation required by lattice vector quantization with a simpler symbol allocation and selection process. Instead of performing mathematical matrix operations during decompression, the system simply selects the appropriate portion of the symbol sequence corresponding to each data value, dramatically simplifying the decompression process while maintaining the ability to adjust accuracy dynamically.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If lattice quantization is used for co-compression, then accuracy adjustment is possible, but the truncation problem arises where some reconstruction points fall outside allowable value intervals

Engineering Contradiction:

Improveaccuracy of data value representationVSAvoidvalidity of reconstruction points

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent changes the fundamental parameter representation from continuous mathematical coordinates requiring matrix transformation to discrete symbol sequence allocation. By representing data values as selections from a symbol sequence rather than through matrix multiplication, the system ensures that all reconstructed values remain within valid intervals, eliminating the truncation problem inherent in lattice quantization approaches.

Inventive Principle:

Principle #35Parameter changes

4Measurement precision

If separate compression is used for each data value, then each value maintains its own accuracy, but compression efficiency is reduced

Engineering Contradiction:

Improveaccuracy of data value representationVSAvoidcompression efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent merges the compression of multiple data values into a single unified symbol sequence. Instead of compressing each data value separately, the system creates one symbol sequence from which portions can be allocated to represent different data values. This merging approach improves compression efficiency by exploiting correlations between data values while still allowing each value to maintain its required accuracy through appropriate symbol allocation.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS9143160B2Co-compression and co-decompression of data values

Publication Date: 2015.09.22 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

AI summary

A first and a second data value are co-compressed by generating a sequence of symbols having a most significant symbol that is the most significant symbol of a compressed representation of the first data value and a least significant symbol that is the most significant symbol of a compressed representation of the second data value. The compressed representation of the first data value corresponds to at least a portion of the symbols of the sequence of symbols starting from the most significant symbol and extending towards the least significant symbol in a first reading direction. The compressed representation of the second data value also corresponds to at least a portion of the symbols of the sequence of symbols, however, starting from the least significant symbol and extending in an opposite reading direction towards the most significant symbol.