Audio Signal Decoding with Grouped Entropy Coding
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Solution Overview
Problem
Current signal compression and recovery techniques face limitations in maximizing transmission efficiency, especially in complex communication environments, and there is a need for enhanced processing schemes to improve data coding and entropy coding efficiency.
Innovation Solution
The method involves a system with data grouping, encoding, and entropy encoding using Pulse Code Modulation (PCM), Pilot-Based Coding (PBC), and Differential Coding (DIFF) schemes, along with variable length encoding and multiplexing, to optimize data transmission efficiency by selecting the most efficient coding schemes based on data characteristics and grouping methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional signal compression techniques are used, then data transmission is achieved, but transmission efficiency is insufficient in complex communication environments
Solution Approach 1:
The patent segments audio signals into multiple frequency bands and processes each band independently using different coding schemes. This segmentation allows the system to adapt to varying communication conditions for different frequency components, improving overall transmission efficiency while maintaining adaptability to complex communication environments.
Solution Approach 2:
The patent employs dynamic selection of coding schemes (PCM, PBC, DIFF) based on current communication conditions and data characteristics. The system dynamically adjusts the coding approach for different frequency bands and time frames, enabling optimal transmission efficiency under varying communication environments rather than using a static coding method.
2Quantity of substance
If data is compressed with high compression rates, then transmission bandwidth is reduced, but audio or video quality may deteriorate
Solution Approach 1:
The patent applies different coding schemes to different frequency bands based on their specific characteristics. Important frequency bands with high perceptual significance use more robust coding methods to preserve audio quality, while less critical bands use higher compression. This local differentiation of quality levels achieves high overall compression while maintaining perceived audio fidelity.
Solution Approach 2:
The patent changes coding parameters dynamically based on the importance and characteristics of different frequency bands. By adjusting compression parameters locally for each band rather than applying uniform compression, the system achieves high compression rates overall while preserving audio quality in critical frequency regions.
3Productivity
If multiple coding schemes are used to improve efficiency, then transmission efficiency increases, but system complexity increases
Solution Approach 1:
The patent divides the audio signal into multiple frequency bands and applies different coding schemes to each segment. This segmentation strategy improves coding efficiency by matching coding methods to specific frequency characteristics, while the modular segmented structure actually simplifies the overall system architecture compared to attempting to process all frequencies with a single complex scheme.
Solution Approach 2:
The patent uses dynamic selection among multiple coding schemes (PCM, PBC, DIFF) based on current data characteristics and communication conditions. This dynamic approach improves coding efficiency by choosing the most appropriate method for each situation, while the selection mechanism itself provides a manageable complexity level through rule-based decision making rather than requiring all schemes to operate simultaneously.
Data Source
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AI summary
An apparatus for processing a signal and method thereof are disclosed. Data coding and entropy coding are performed with interconnection, and grouping is used to enhance coding efficiency. The present invention includes the steps of obtaining index information and entropy- decoding the index information and identifying a content corresponding to the entropy-decoded index information and selecting entropy table.