Quasi-Periodic Signal Decomposition for Variable Frequency Tracking
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Solution Overview
Problem
Existing digital representation methods for waveforms face challenges in efficiently capturing and storing high-fidelity signals, leading to large storage needs and wasted processing bandwidth due to over-sampling of repetitive data, which does not convey meaningful information.
Innovation Solution
A method and apparatus using a system of overlapping bandpass filters with closely spaced center frequencies to track frequency components of quasi-periodic waveforms, allowing for efficient digital filtering and wavelet transforms, and tracking frequency variations over a wide range, such as in ECG or seismic signals, by selecting the strongest signal within overlapping filter banks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high-fidelity digital representation methods are used to capture waveforms, then signal integrity is improved, but storage requirements increase and processing bandwidth is wasted due to over-sampling of repetitive data
Solution Approach 1:
The patent extracts only the meaningful non-repetitive components of waveforms by decomposing signals into periodic and transient parts. The periodic components are identified and separated, leaving only the essential transient information for storage and processing, thereby reducing storage requirements while preserving signal integrity.
Solution Approach 2:
The patent discards repetitive periodic waveform data that can be regenerated or inferred, while recovering and preserving only the essential transient components. This selective discarding of redundant information reduces storage and processing requirements without losing critical signal characteristics.
2Ease of manufacture
If traditional digital filtering methods are used, then implementation is simple, but frequency tracking precision deteriorates for quasi-periodic waveforms with varying frequencies
Solution Approach 1:
The patent implements dynamic filter banks where filter characteristics adapt to track the instantaneous frequency of quasi-periodic waveforms. The filter bank structure allows continuous adjustment of center frequencies and bandwidths to follow frequency variations, achieving precise frequency tracking while maintaining practical implementability through systematic design.
Solution Approach 2:
The patent transitions from single-filter approaches to multi-dimensional filter bank structures with multiple stages and parallel paths. This dimensional expansion enables simultaneous coverage of multiple frequency ranges with overlapping bands, improving frequency tracking precision through coordinated analysis across different frequency dimensions.
3Device complexity
If filter banks with widely spaced center frequencies are used, then processing complexity is reduced, but frequency resolution deteriorates
Solution Approach 1:
The patent merges multiple filter banks with overlapping frequency ranges into a unified structure. The overlapping bands are coordinated to provide continuous frequency coverage, where adjacent filters share transition regions. This merging approach achieves high frequency resolution through dense spectral sampling while managing processing complexity through systematic organization and resource sharing.
Data Source
AI summary
A system and method for representing quasi-periodic waveforms, for example, representing a plurality of limited decompositions of the quasi-periodic waveform. 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 quasi-periodic waveform. Data-structure attributes are created and used to reconstruct the quasi-periodic waveform. Features of the quasi-periodic wave are tracked using pattern-recognition techniques. The fundamental rate of the signal (e.g., heartbeat) can vary widely, for example by a factor of 2-3 or more from the lowest to highest frequency. To get quarter-phase representations of a component (e.g., lowest frequency “rate” component) that varies over time (by a factor of two to three) many overlapping filters use bandpass and overlap parameters that allow tracking the component's frequency version on changing quarter-phase basis.