Quasi-Periodic Waveform Segmentation for Low-Volume Signal Analysis
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Solution Overview
Problem
High-fidelity digital representations of waveforms require large storage and processing bandwidth, leading to inefficiencies in data storage and transmission, as they often include insignificant data that does not contribute to meaningful analysis.
Innovation Solution
A method for decomposing quasi-periodic waveforms into component signals, filtering out insignificant data, and reconstructing the waveform using a data structure that efficiently stores and transmits only significant features, utilizing bandpass filters and data structures with phase-adjusted amplitude values to maintain signal integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high-fidelity digital representation is used, then signal integrity is maintained, but storage and processing bandwidth requirements increase
Solution Approach 1:
The signal is divided into multiple segments or components, each representing different frequency bands or time intervals. This segmentation allows the system to process and store only the significant portions of the signal that contribute to meaningful analysis, rather than preserving every detail of the original high-fidelity signal.
Solution Approach 2:
The system extracts and removes insignificant data components from the signal representation. By identifying and eliminating redundant or non-contributory signal elements, the patent reduces data volume while maintaining the integrity of the meaningful signal features needed for analysis.
2Measurement precision
If high-fidelity digital representation is used, then accurate waveform detection is achieved, but processing bandwidth and power consumption increase
Solution Approach 1:
The system applies partial action by processing only the essential components of the signal that are necessary for accurate waveform detection. Rather than processing the entire high-fidelity signal, the patent focuses computational resources on the critical features that contribute to detection accuracy, thereby reducing power consumption.
3Adaptability or versatility
If complete waveform data is stored, then comprehensive analysis is possible, but storage space requirements increase
Solution Approach 1:
The system extracts and retains only the significant features and characteristics of the waveform that are necessary for comprehensive analysis. By removing redundant data while preserving the essential analytical information, the patent enables versatile waveform analysis within reduced storage constraints.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces storage and processing requirements while maintaining signal fidelity, allowing for effective analysis and transmission of waveforms by focusing on significant features and reducing unnecessary data.
Implementation Method 1
utilizing bandpass filters and data structures with phase-adjusted amplitude values to maintain signal integrity
Data Source
AI summary
The present invention provides a system and method for representing quasi-periodic (“qp”) waveforms comprising, representing a plurality of limited decompositions of the qp waveform, wherein each decomposition includes a first and second amplitude value and at least one time value. In some embodiments, each of the decompositions is phase adjusted such that the arithmetic sum of the plurality of limited decompositions reconstructs the qp waveform. These decompositions are stored into a data structure having a plurality of attributes. Optionally, these attributes are used to reconstruct the qp waveform, or patterns or features of the qp wave can be determined by using various pattern-recognition techniques. Some embodiments provide a system that uses software, embedded hardware or firmware to carry out the above-described method. Some embodiments use a computer-readable medium to store the data structure and/or instructions to execute the method.