Encoder Pulse Vector Coding Frequency Range
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Solution Overview
Problem
At low bit rates, the number of spectrum coefficients to be encoded exceeds the number of pulses in pulse vector coding, leading to poor sound quality due to insufficient bit allocation, resulting in a large portion of the spectrum remaining unencoded.
Innovation Solution
An encoder and decoder configuration that includes a time-frequency conversion section, an effective range specifying section, and a pulse vector coding section, which performs pulse vector coding only on a signal component within a specified effective range in the frequency domain, improving bit efficiency and decoded signal quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pulse vector coding is applied to all spectrum coefficients in the frequency domain, then the encoding coverage is maximized, but the number of bits required for encoding becomes excessively large at low bit rates
Solution Approach 1:
The frequency domain signal is segmented into multiple frequency bands, and pulse vector coding is applied selectively to specific bands rather than uniformly across the entire spectrum. This segmentation allows the system to concentrate encoding resources on bands containing important signal components while reducing or eliminating coding in less important bands, thereby resolving the contradiction between encoding coverage and bit rate consumption.
Solution Approach 2:
Different encoding strategies are applied to different frequency bands based on their local characteristics. Bands containing significant signal energy or important information are encoded with higher precision using pulse vector coding, while bands with less important content are encoded with lower precision or skipped entirely. This local differentiation optimizes the allocation of limited bits to achieve better overall reconstruction quality at low bit rates.
2Manufacturing precision
If the number of pulses is increased to encode more spectrum coefficients, then the decoded signal quality improves, but the bit rate requirement increases
Solution Approach 1:
Instead of attempting to encode all spectrum coefficients uniformly, the system applies pulse vector coding selectively to only the most important frequency bands. This partial action approach encodes sufficient information to achieve acceptable or good decoded quality for the most critical parts of the signal, while accepting that less important parts will be reconstructed with lower fidelity or not at all, thereby achieving reasonable quality at low bit rates.
3Loss of information
If pulse vector coding is applied to the entire frequency spectrum, then the spectral representation is complete, but the bit efficiency becomes insufficient at low bit rates
Solution Approach 1:
The system extracts and identifies the most important frequency bands from the complete spectrum that contain the essential signal information. By taking out only these critical bands for pulse vector coding while excluding or coarsely encoding the rest, the system maintains the necessary spectral representation for acceptable signal reconstruction while dramatically improving bit efficiency. This extraction approach allows low bit rate operation without complete spectral loss.
Data Source
AI summary
An encoder whereby the bit efficiency of encoding can be improved, thereby improving the qualities of signals as decoded. In the encoder: a time-frequency converting unit (101) converts signals, which are to be encoded, to frequency domain signals; an adaptive spectrum formation encoding unit (102) determines an effective range in the frequency band of the frequency domain signals; and a pulse vector encoding unit (103) pulse vector encodes only the signal components within the effective range.