Signal Analysis Transient Information Extraction
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Solution Overview
Problem
Multidimensional signals often contain transient information that complicates processing and compression due to variability along stable dimensions, leading to increased information entropy and difficulty in distinguishing real details from noise.
Innovation Solution
A Stable-Transient Separator (STS) method that separates transient information from stable information in multidimensional signals, using moving averages and precision weights to preserve real details while reducing noise and variability, allowing for improved compression and encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transient information is included in the signal to preserve all details, then measurement precision is improved, but information entropy increases making compression difficult
Solution Approach 1:
The patent segments the signal into two distinct components: a stable core signal representing predictable information, and a transient layer representing unpredictable variations. This segmentation allows each component to be processed differently - the core signal can be compressed efficiently while the transient layer is preserved separately, resolving the contradiction between preserving detail accuracy and reducing information entropy.
Solution Approach 2:
The patent extracts the transient information from the overall signal by comparing successive signal samples and identifying deviations from the stable pattern. This extracted transient layer can then be handled separately, allowing the core signal to be compressed without the entropy burden of transient variations, while still preserving complete signal information.
2Productivity
If transient information is removed to reduce information entropy, then compression efficiency is improved, but signal fidelity deteriorates
Solution Approach 1:
By segmenting the signal into core and transient components, the patent enables independent compression of the core signal while preserving the transient layer. This maintains signal fidelity because both components can be retained and recombined, while achieving improved compression efficiency on the compressible core portion.
Solution Approach 2:
The patent changes the representation parameters of the signal by separating it into different domains - the core signal in a compressed domain and the transient layer in a residual domain. This parameter transformation allows efficient compression without sacrificing fidelity, as the transient information can be reconstructed and added back.
3Measurement precision
If signal processing includes all variations to maintain accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent simplifies processing complexity by segmenting signal analysis into two distinct stages: core signal extraction using stable patterns, and transient layer identification using deviation detection. This segmentation allows each stage to use specialized, optimized algorithms rather than applying complex general-purpose processing to the entire signal.
Solution Approach 2:
The patent introduces an intermediary transient layer that mediates between the core signal and the full original signal. This intermediary structure simplifies processing by providing a clear separation point where stable patterns are processed one way and transient variations are processed differently, reducing overall system complexity.
4Device complexity
If successive signal samples are processed independently to maintain simplicity, then device complexity is reduced, but loss of information increases due to inability to exploit temporal stability
Solution Approach 1:
The patent maintains continuity of useful action by using the stable patterns identified in previous signal samples to inform processing of current samples. The core signal extraction process continuously leverages temporal stability, allowing simple local operations to accumulate into powerful compression without requiring complex inter-sample processing.
Solution Approach 2:
The signal processing system performs self-service by using its own identified stable patterns as the basis for compression. The core signal representation naturally captures temporal redundancy, and the transient layer automatically captures deviations, allowing the system to exploit temporal stability through its inherent structure rather than complex external processing.
Data Source
AI summary
A signal processor receives settings information. The settings information specifies a setting of a given element for each image in a sequence of multiple images in which the given element resides. The signal processor also receives precision metadata specifying an estimated precision of each of the settings of the given element for each image in the sequence. Based on the settings information and the precision metadata, the signal processor generates a setting value for the given element. If the setting value produced for the given element is relatively stable, and thus likely a better representation of a setting for the given element than a current setting of the given element, the signal processor utilizes the generated setting value instead of the current setting for encoding purposes.