Secondary Path Modeling for Active Noise Control
First Claim
1. A method for modeling a secondary path for an active noise control system, comprising:
- receiving a reference signal;
filtering the reference signal with an initial secondary path model to obtain a filtered reference signal;
calculating an autocorrelation matrix from the filtered reference signal;
calculating a plurality of eigenvalues from the autocorrelation matrix;
calculating a maximum difference between the plurality of eigenvalues;
iterating a test model to determine an optimized secondary path model having a plurality of optimized eigenvalues that have a minimized difference that is less than the maximum difference of the plurality of eigenvalues, wherein the optimized secondary path model may be utilized in the active noise control system.
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Abstract
Methods for modeling the secondary path of an ANC system to improve convergence and tracking during noise control operation, and their associated uses are provided. In one aspect, for example, a method for modeling a secondary path for an active noise control system is provided. Such a method may include receiving a reference signal, filtering the reference signal with an initial secondary path model to obtain a filtered reference signal, calculating an autocorrelation matrix from the filtered reference signal, and calculating a plurality of eigenvalues from the autocorrelation matrix. The method may further include calculating a maximum difference between the plurality of eigenvalues and iterating a test model to determine an optimized secondary path model having a plurality of optimized eigenvalues that have a minimized difference that is less than the maximum difference of the plurality of eigenvalues, such that the optimized secondary path model may be utilized in the active noise control system.
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Citations
20 Claims
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1. A method for modeling a secondary path for an active noise control system, comprising:
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receiving a reference signal; filtering the reference signal with an initial secondary path model to obtain a filtered reference signal; calculating an autocorrelation matrix from the filtered reference signal; calculating a plurality of eigenvalues from the autocorrelation matrix; calculating a maximum difference between the plurality of eigenvalues; iterating a test model to determine an optimized secondary path model having a plurality of optimized eigenvalues that have a minimized difference that is less than the maximum difference of the plurality of eigenvalues, wherein the optimized secondary path model may be utilized in the active noise control system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 15, 16, 17)
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10. A method for modeling a secondary path for an active noise control system, comprising:
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obtaining an initial secondary path model; and calculating an updated secondary path model that maintains phase of the initial secondary path model, but equalizes the magnitude of the initial secondary path model. - View Dependent Claims (11, 12, 13, 14, 18, 19, 20)
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Specification