Subband Adaptive Filter Coefficient Correction for Acausal Paths
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Solution Overview
Problem
Subband adaptive filter systems face instability when dealing with acausal components in the plant model, leading to uncontrolled growth of coefficients and potential overflow errors, which affects their performance in noise cancellation applications.
Innovation Solution
The implementation of an inverse stacking process that corrects coefficients corresponding to acausal components, allowing the subband adaptive filter system to adapt at a decimated rate and selectively activate or deactivate frequency bands, thereby reducing computational load and preventing artifacts outside the target frequency range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the subband adaptive filter system processes all frequency bands including those with acausal components, then the system can maintain broader frequency coverage, but coefficient uncontrolled growth and instability occur
Solution Approach 1:
The frequency spectrum is divided into multiple subbands, and the system selectively activates only those subbands that correspond to causal transfer function components. This segmentation allows the system to maintain stability by excluding acausal subbands while preserving coverage of beneficial frequency ranges.
Solution Approach 2:
Different quality characteristics are applied to different frequency subbands. Causal subbands are fully processed for noise cancellation, while acausal subbands are either excluded or processed with reduced adaptation. This local differentiation maintains overall system stability while preserving performance in reliable frequency regions.
2Manufacturing precision
If the subband adaptive filter adapts at full sampling rate, then the convergence rate improves, but the computational load increases
Solution Approach 1:
The adaptive filter operates at a decimated (reduced) sampling rate rather than full sampling rate. This periodic downsampling reduces the number of computations required per unit time while still achieving effective noise cancellation in the target frequency bands, thereby lowering computational load and energy consumption.
3Adaptability or versatility
If the system processes frequency bands outside the target range, then broader noise cancellation coverage is achieved, but artifacts affect overall system performance
Solution Approach 1:
The system extracts and processes only the frequency subbands that correspond to the target frequency range and causal transfer function components. Frequency bands outside the target range or associated with acausal components are excluded from processing, preventing the generation of harmful artifacts while maintaining effective noise cancellation within the desired frequency range.
Data Source
AI summary
A noise reduction system includes sensors configured to generate an input signal, an adaptive filter configured to represent a transfer function of a path traversed by the input signal, one or more processing devices, and one or more transducers. The processing devices receive the input signal and generate an updated set of filter coefficients of the adaptive filter by separating the input signal into frequency subbands; determining for each subband, coefficients of a corresponding subband adaptive module; and combining the coefficients of multiple subband adaptive modules. Determining the coefficients of the corresponding subband adaptive module includes selecting a subset of a precomputed set of filter coefficients of the adaptive filter. The processing devices process a portion of the input signal using the updated set of filter coefficients of the adaptive filter to generate an output that destructively interferes with another signal traversing the path represented by the transfer function.