Vector Indexing by Leader Class Segmentation for Lower Complexity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current algorithms for indexing and de-indexing in speech and audio coding, particularly in lattice structures, face challenges in reducing complexity while maintaining coding efficiency, especially in mobile terminal communications.
Innovation Solution
A method is introduced that adapts processing based on specific characteristics of pre-defined groups of leader classes, applying specialized processing for input vectors within these groups and general processing for those outside, thereby reducing overall complexity by simplifying the indexing and de-indexing procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If general processing is applied to all input vectors, then all vectors can be indexed correctly, but computational complexity increases
Solution Approach 1:
The patent segments the codebook into multiple leader classes with different characteristics. By dividing the general processing task into specific subsets (leader classes with specific properties), the system applies tailored processing to each segment, reducing overall computational complexity while maintaining indexing accuracy for all vectors.
Solution Approach 2:
The patent applies different processing strategies to different leader classes based on their local characteristics. Leader classes with specific properties (e.g., those with certain symmetry or structure) receive optimized processing, while others receive standard processing. This local differentiation reduces computational complexity without sacrificing reliability.
2Device complexity
If simplified processing is applied to reduce complexity, then computational load decreases, but indexing precision may deteriorate
Solution Approach 1:
The patent changes processing parameters based on the characteristics of each leader class. By identifying specific properties of leader classes (such as symmetry, dimensionality, or structure), the system adjusts processing parameters to achieve optimal balance between computational complexity and indexing precision for each case.
3Device complexity
If specialized processing is applied to specific leader classes, then complexity is reduced for those classes, but system adaptability decreases
Solution Approach 1:
The patent creates a universal indexing framework that can handle multiple types of leader classes through a common structure. The system identifies characteristics of different leader classes and applies appropriate processing within a unified architecture, maintaining adaptability across diverse cases while reducing complexity through specialization where applicable.
Data Source
AI summary
This invention relates to indexing an input vector contained in a set of vectors of a plurality of sets of vectors. The indexing comprises performing, in case that the input vector is contained in a set of vectors of a pre-defined group of one or more sets of vectors of the plurality of sets of vectors, a specific processing that is adapted to a characteristic of the sets of vectors in the pre-defined group of sets of vectors and is only applicable in case of input vectors contained in sets of vectors with the characteristic. The indexing further comprises performing, in case that the input vector is not contained in a set of vectors of the pre-defined group of sets of vectors, a general processing. The invention further relates to an according determining of a target vector contained in a set of vectors of a plurality of sets of vectors based on an index associated with said target vector.