Signal Processing Method for Continuous Real-Time Output
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Solution Overview
Problem
Existing methods for combining time segments of digital signals to produce a continuous output often introduce signal artefacts, especially around the ends of time windows, and struggle to operate in real-time due to processing demands, particularly when dealing with significant and fast changes in the input signal.
Innovation Solution
A method that combines multiple simultaneous signals by determining the strength of a periodic component in each signal, weighting them based on this strength, and summing the unfiltered signals, which avoids artefacts created by filtering and allows real-time processing by focusing on signals with strong periodic components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If existing methods are used to stitch signal segments together to provide a continuous output signal, then a continuous output is achieved, but signal artefacts are introduced particularly around the end of time windows
Solution Approach 1:
The patent extracts only the periodic component from each signal segment using spectral analysis, separating it from the aperiodic content. By combining only the periodic components, the method avoids introducing artefacts that would result from combining entire signal segments including their transient boundaries.
Solution Approach 2:
The patent applies different processing strategies to different frequency components of the signal. The periodic components are extracted and combined with phase alignment, while aperiodic components are handled separately or discarded, ensuring that each component is treated according to its characteristics.
2Stability of the object's composition
If existing methods are used to stitch signal segments together, then a continuous output is achieved, but the output does not faithfully follow the input where there are significant and fast changes
Solution Approach 1:
The patent dynamically adjusts the weighting of different signal segments based on their periodicity strength and phase relationships. When significant changes occur in the input signal, the method adapts by re-evaluating the periodic components and their contributions, ensuring the output faithfully follows the input while maintaining continuity.
Solution Approach 2:
The patent changes the parameters used for combining signals based on the characteristics of the input. The weighting factors and phase alignments are adjusted according to the strength and consistency of periodic components detected in each segment, allowing faithful representation of both steady-state and transient behaviors.
3Stability of the object's composition
If existing methods are used to stitch signal segments together, then a continuous output is achieved, but real-time processing cannot be accomplished due to the amount of processing required
Solution Approach 1:
The patent extracts only the essential periodic components from each signal segment using efficient spectral methods, discarding the computationally intensive aperiodic content. This extraction approach dramatically reduces the processing required for combining segments while maintaining the continuity of the output signal.
Solution Approach 2:
The patent applies partial processing by focusing only on the periodic components that are most relevant for continuous signal reconstruction. Rather than processing entire signal segments, the method selectively processes only the necessary periodic parts, reducing computational load while achieving real-time capability.
4Measurement precision
If signals are filtered before combining to remove artefacts, then signal quality is improved, but filtering itself can create artefacts when there are significant changes in the input signal
Solution Approach 1:
The patent inverts the conventional approach by not filtering the entire signal before combining, but rather extracting periodic components in the frequency domain and then reconstructing the combined signal. This inversion avoids the artefacts that conventional time-domain filtering would introduce during signal transitions.
Solution Approach 2:
The patent applies filtering selectively only to the periodic components in the frequency domain, rather than applying broad time-domain filtering to the entire signal. This localized frequency-domain filtering improves signal quality while avoiding the artefacts that result from aggressive time-domain filtering during significant signal changes.
Data Source
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AI summary
A method and apparatus which combines multiple simultaneous signals thought to contain a common periodic component by performing principal component analysis on each of the multiple signals, finding the weight of the first principal component, and then adding the multiple signals together in a weighted sum according to the weight of the first principal component. The method and apparatus further includes a way of combining signals from successive overlapping time windows in real time by differentiating the signal and forming as each output signal sample the value of the preceding signal sample summed with the differential of the signal, weighted by weights based on the amplitude of the differential signal at that time point.