Adaptive Filter Adaptation Rate Adjustment for Active Noise Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Active noise reduction systems using adaptive filters face challenges in achieving complete noise elimination due to limitations in adapting to frequency changes and leakage factors, leading to incomplete noise attenuation.
Innovation Solution
The system determines an adaptation rate for adaptive filters based on frequency-related parameters of the reference input signal and applies it to filter coefficients, while also using leakage factors adjusted by a leakage adjuster to optimize noise reduction, implemented through digital signal processing circuitry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed adaptation rate is used in the adaptive filter, then the system is simple to implement, but the noise reduction performance deteriorates when frequency changes occur
Solution Approach 1:
The patent implements dynamic adaptation rate adjustment by making the adaptation rate variable based on the frequency characteristics of the reference input signal. The system continuously monitors frequency-related parameters and adjusts the adaptation rate accordingly, transforming a static parameter into a dynamic one that adapts to changing conditions, thereby resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The patent changes the adaptation rate parameter based on frequency-related parameters of the reference input signal. By establishing a relationship between the adaptation rate and frequency characteristics (such as using the frequency itself or rate of change of frequency as control parameters), the system optimizes noise reduction performance across different operating conditions while maintaining a relatively simple implementation structure.
2Productivity
If the adaptation rate is increased to improve noise attenuation speed, then noise reduction efficiency improves, but system stability deteriorates
Solution Approach 1:
The patent uses dynamic adaptation rate adjustment based on frequency characteristics to balance speed and stability. By making the adaptation rate variable rather than fixed, the system can increase the adaptation rate when conditions permit (improving noise reduction speed) while automatically reducing it when stability concerns arise, thus resolving the contradiction between productivity and reliability.
Solution Approach 2:
The patent establishes a controlled relationship between the adaptation rate and frequency-related parameters, allowing the adaptation rate to change within optimized bounds. This parameter change strategy enables faster noise reduction when frequency conditions are favorable while maintaining stability through controlled adjustment limits and frequency-based modulation, resolving the speed-stability trade-off.
3Measurement precision
If leakage factors are applied to filter coefficients to improve adaptation accuracy, then noise attenuation performance improves, but the system becomes more complex
Solution Approach 1:
The patent combines the leakage factor application with the existing adaptive filter coefficient update process. By integrating the leakage compensation mechanism into the standard LMS (Least Mean Squares) algorithm framework, the system achieves improved adaptation accuracy without requiring a completely separate processing path, thus minimizing the increase in system complexity while gaining measurement precision.
Solution Approach 2:
The patent implements a self-adjusting leakage factor mechanism that automatically adapts to the input signal characteristics. The leakage factors are determined based on the frequency-related parameters of the reference input signal, allowing the system to self-regulate the amount of leakage compensation needed without external intervention, thereby improving accuracy while keeping the control mechanism relatively simple.
Data Source
Figure 1A
Figure 1B
Figure 2A~2B
AI summary
A method for determining leakage factors or adaptation rates, or both, for adaptive filters in an active noise reduction system. The leakage factor or adaptation rate, or both, may vary depending on a parameter of an input reference signal. The parameter may include one or more of reference signal input frequency, rate of change of reference input signal frequency, if a predetermined triggering condition exits, or if a predetermined event has occurred.