Two-Channel Quadrature Mirror Filter Bank Matrix Decomposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing two-channel quadrature mirror filter banks (2c-QMFB) require high-order FIR filters, leading to significant hardware resource consumption without adequately addressing frequency domain performance.
Innovation Solution
Implement a matrix decomposition structure for the 2c-QMFB, utilizing an efficient polyphase structure based on time division multiplexing, which decomposes the analysis and synthesis filter parts into modules with reduced multipliers and adders through SVD decomposition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-order FIR filters are used in the analysis and synthesis filter parts to meet high frequency domain performance requirements, then the frequency domain performance is improved, but the hardware resource consumption increases significantly
Solution Approach 1:
The filter bank is divided into analysis filter part and synthesis filter part, each further segmented into multiple polyphase components. The segmentation allows independent optimization of each component, reducing the hardware resources needed while maintaining overall frequency domain performance through coordinated operation of the segmented parts.
Solution Approach 2:
The patent transforms the traditional time-domain filter implementation into a matrix decomposition structure in the frequency domain. By representing filter coefficients as matrices and using singular value decomposition (SVD), the system achieves the same filtering function with reduced computational complexity and hardware resources, effectively adding a mathematical dimension to the problem solution.
2Reliability
If high-order FIR filters are used to achieve better signal decomposition and reconstruction, then the signal processing quality is improved, but the complexity of the device structure increases
Solution Approach 1:
The patent changes the representation parameters of the filter coefficients from traditional time-domain sequences to frequency-domain matrices obtained through SVD decomposition. This parameter transformation allows the system to achieve the same signal processing quality with fewer coefficients and simpler structural parameters, directly reducing device complexity while maintaining reliability.
Solution Approach 2:
The patent extracts and retains only the most significant components from the full filter decomposition. By using SVD decomposition and keeping only the dominant singular values and corresponding eigenvectors, the system removes redundant computational elements while preserving the essential signal processing functionality, thus reducing structural complexity without compromising reconstruction quality.
Data Source
AI summary
A matrix decomposition structure of a two-channel quadrature mirror filter bank, including an analysis filter part, a synthesis filter part, the filter part includes an E0,M module, an X module, a Y module, a Z module, an input port and an output port. The X module takes a value of the input port as an input of a multiplier, and the E0,M module delays the input. An output of the Xmodule passes through the Y module and then is used as an input of the Z module, and outputs of the Z module and the E0,M module are added and then output from the output port, and pass through a middle part to enter the synthesis filter part.