Noise Suppression System Using A Priori S/N Ratio Correction
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Solution Overview
Problem
Existing noise suppression technologies face accuracy issues due to fluctuations in noise magnitude when separating desired signals from mixed input signals.
Innovation Solution
A noise suppression system that includes an a priori S/N ratio estimated value and expectation calculation unit, a noise suppression coefficient calculation unit, and a noise suppression unit, which corrects the estimated S/N ratio using a priori S/N ratio models or signal and noise models to calculate a noise suppression coefficient for effective noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise suppression is performed using traditional methods, then noise can be reduced, but accuracy decreases when noise magnitude fluctuates
Solution Approach 1:
The system dynamically adjusts the noise suppression coefficient based on the estimated a priori S/N ratio. The coefficient calculation unit computes different suppression coefficients for different noise levels, allowing the system to adapt to fluctuating noise magnitudes in real-time while maintaining high suppression accuracy across varying conditions
Solution Approach 2:
The invention changes the parameter of noise suppression coefficient based on the estimated a priori S/N ratio. By calculating the coefficient as a function of the S/N ratio (e.g., using formulas like 1/(1+exp(-a*(S/N-r))+exp(-b*(S/N-r))) where r is a threshold), the system adjusts its behavior according to the current noise level, resolving the contradiction between maintaining accuracy and adapting to fluctuations
2Measurement precision
If noise suppression coefficient is fixed, then system complexity is reduced, but noise suppression accuracy decreases under varying noise conditions
Solution Approach 1:
The system performs preliminary estimation of the a priori S/N ratio using the expected signal model and noise model before calculating the noise suppression coefficient. This preliminary action allows the system to prepare appropriate suppression coefficients in advance for different noise conditions, achieving high accuracy without requiring complex real-time adaptive algorithms
Solution Approach 2:
The system uses feedback from the estimated a priori S/N ratio to adjust the noise suppression coefficient. The coefficient calculation unit receives the estimated S/N ratio and computes an appropriate coefficient based on this feedback, creating a closed-loop system that maintains high accuracy while managing complexity through structured feedback mechanisms
Data Source
AI summary
A noise suppression system includes an a priori S/N ratio estimated value and expectation calculation unit that acquires an expectation of a priori S/N ratio, by correcting an estimated value of the a priori S/N ratio relating to a signal and a noise based on a priori S/N ratio model or based on a signal model and a noise model, the signal and the noise being estimated from an input signal in which the signal and the noise are mixed; a noise suppression coefficient calculation unit that calculates a noise suppression coefficient with use of the expectation of the a priori S/N ratio; and a noise suppression unit that suppresses the noise included in the input signal by multiplying the input signal by the noise suppression coefficient.