Noise Suppression Using Mixed Noise Information
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Solution Overview
Problem
Existing noise suppression technologies are ineffective for highly nonstationary signals with varying characteristics, as they rely on a single noise characteristic and struggle with noise types like impact noise and spectral peaks.
Innovation Solution
A method that analyzes noisy signals to generate mixed noise information by combining multiple noise characteristics, allowing for adaptive noise suppression across various frequency components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single noise characteristic is used for noise suppression, then the method is simple and easy to implement, but it cannot effectively suppress highly nonstationary signals with varying characteristics such as impact noise and spectral peaks
Solution Approach 1:
The patent segments noise information into multiple characteristics (e.g., average spectrum, maximum spectrum, minimum spectrum, or different statistical parameters) and processes each segment separately. This allows the system to capture different aspects of noise behavior and adapt to varying noise types including nonstationary signals, while maintaining a structured and manageable processing framework.
Solution Approach 2:
The patent creates a universal noise suppression system that can handle multiple noise types (stationary and nonstationary) using a single integrated apparatus. By incorporating multiple noise information characteristics and using analysis means to determine appropriate mixing ratios, the system achieves multi-functionality, adapting to different signal conditions without requiring separate specialized systems for each noise type.
2Measurement precision
If multiple noise information characteristics are mixed to generate mixed noise information, then the noise suppression accuracy improves for nonstationary signals, but the device complexity increases
Solution Approach 1:
The patent performs preliminary analysis of the input signal to determine the appropriate mixing ratio of noise information characteristics before executing the noise suppression. This preliminary action allows the system to adapt to different signal conditions and select optimal processing parameters in advance, improving accuracy while avoiding the need for complex real-time adjustments during the suppression process.
Solution Approach 2:
The patent uses analysis means to evaluate the input signal characteristics and provides feedback to determine the mixing ratio of noise information. This feedback mechanism enables the system to automatically adjust the processing parameters based on the actual signal conditions, achieving high accuracy for various noise types while maintaining a relatively simple structure through intelligent control.
3Reliability
If noise information is recorded in advance for suppression, then the noise suppression effect is sufficient and distortion is small, but the types of noise that can be suppressed are limited
Solution Approach 1:
The patent combines multiple noise information characteristics (such as average spectrum, maximum spectrum, minimum spectrum, or different statistical parameters) to create composite noise information representations. This composite approach allows the system to model complex nonstationary noise patterns that cannot be captured by single-characteristic noise information, thereby expanding the range of suppressible noise types while maintaining suppression effectiveness and minimizing distortion.
Data Source
AI summary
A signal processing method includes: analyzing a noisy signal that is supplied as an input signal; generating mixed noise information by mixing a plurality of noise information about a noise to be suppressed based on the result of said analysis of the noisy signal; and suppressing the noise using the mixed noise information.