Audio Decoder Dynamic Nyquist Adjustment
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Solution Overview
Problem
Existing audio coding systems face inefficiencies in transforming digital audio signals from one frequency domain to another, as they often use constant sub-sampling factors that do not adapt to variations in the signal, leading to increased computational complexity and potential artifacts.
Innovation Solution
A method in an audio decoder that dynamically adjusts the Nyquist frequency by analyzing spectral content on a frame-by-frame basis, reducing the frequency domain sampling rate when the signal is band-limited, and restoring it through sub-sampling and re-sampling, allowing for adaptive transformation between frequency domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If constant sub-sampling is used to reduce transform size, then computational complexity is reduced, but adaptability to signal variations is lost
Solution Approach 1:
The patent implements dynamic sub-sampling by adjusting the sub-sampling factor based on the analyzed spectral content of each frame. The system transitions from constant sub-sampling to variable sub-sampling where the factor changes adaptively according to signal characteristics, resolving the contradiction between computational efficiency and adaptability.
Solution Approach 2:
The patent changes the sub-sampling parameter dynamically based on spectral analysis results. By modifying the sub-sampling factor according to the identified frequency range and spectral density, the system achieves both computational efficiency and adaptability to varying signal conditions.
2Productivity
If sub-sampling is applied to band-limited signals, then transform size is reduced, but artifacts may be introduced
Solution Approach 1:
The patent performs preliminary spectral analysis before applying sub-sampling to identify the actual frequency range of the signal. This preliminary action ensures that sub-sampling is applied appropriately only when the signal is band-limited, preventing artifacts while still achieving transform size reduction.
Solution Approach 2:
The system uses feedback from spectral analysis to control the sub-sampling process. The identified frequency range and spectral characteristics provide feedback that determines whether and how much sub-sampling to apply, ensuring artifact-free processing while maintaining efficiency.
Data Source
AI summary
There is provided an audio decoder and a method therein for transforming a digital audio signal from a first frequency domain to a second frequency domain. For each received frame of the digital audio signal, the method identifies an upper limit of the frequency range, and if the upper limit of the frequency range is below the Nyquist frequency of said frame of the digital audio signal by more than a threshold amount, the Nyquist frequency of said frame of the digital audio signal is lowered from its original value to a reduced value by removing spectral bands of said frame of the digital audio signal above the identified upper limit of the frequency range. Thereafter said frame of the digital audio signal is transformed from the first frequency domain to the second frequency domain via an intermediate time domain.