Frequency-Bin Noise Cancellation for Peak and Notch Bands
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional active noise control techniques require high computational load for updating filter coefficients and are ineffective in environments with peak and notch bands in transmission characteristics, which hampers the muting effect.
Innovation Solution
A signal processing device with a muting filter that sets update parameters for frequency bins differently based on their roles in noise cancellation, avoiding updates in notch bands and optimizing updates in peak bands to reduce computational load and enhance noise cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filter coefficients are updated for all frequency bins using LMS algorithm, then noise cancellation accuracy is improved, but computational load increases
Solution Approach 1:
The frequency spectrum is divided into multiple frequency bins, and the update parameter for each frequency bin is independently controlled. This segmentation allows selective updating of only necessary frequency bins, reducing overall computational load while maintaining noise cancellation accuracy for relevant frequencies
Solution Approach 2:
Different update parameters are assigned to different frequency bins based on their characteristics. Frequency bins corresponding to actual noise components use larger update parameters for accurate tracking, while bins in notch bands use smaller or zero update parameters to avoid unnecessary computation and instability
2Speed
If update parameter is increased for faster coefficient convergence, then adaptation speed is improved, but stability deteriorates in notch bands
Solution Approach 1:
The update parameter is locally optimized for each frequency bin based on the transmission characteristics. In notch bands where stability is critical, smaller update parameters are used to prevent oscillation, while in peak bands or noise frequency bands, larger update parameters enable faster adaptation without compromising overall system stability
Data Source
AI summary
Provided are a signal processing device, a program, a range hood device, and a selection method for frequency bins in a signal processing device with which it is possible to reduce the load on computation processing for computing filter coefficients and provide an excellent muting effect even when there are a peak band and a notch band in transmission characteristics from a speaker to an error microphone. A parameter setter sets an update parameter μ such that a filter coefficient W is corrected, only for a first frequency bin that corresponds to a frequency band of a first noise and a second frequency bin that corresponds to a frequency band of a second noise.