Signal Reconstruction Using Codec Likelihood to Avoid Noise Removal Apparatus
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing signal reconstruction methods face challenges in accurately reconstructing signals without using a noise removal apparatus, especially when the observation process matrix is singular, leading to issues with data fidelity and model definition.
Innovation Solution
A signal reconstruction method and apparatus that utilize a codec to consider the likelihood of the input signal being a predetermined type, executing coding on processing results to reconstruct signals with desired characteristics, even without a defined noise removal model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a noise removal apparatus is used to define the model s(x), then the likelihood of the reconstructed signal being a predetermined type of signal can be accurately defined, but the device complexity and processing requirements increase significantly
Solution Approach 1:
The patent extracts the essential function of the noise removal apparatus (defining signal likelihood through coding characteristics) and separates it from the complex apparatus itself. By using a codec to execute coding on the processing result and determine likelihood based on coding characteristics, the invention achieves model definition without requiring a dedicated noise removal apparatus, thus reducing device complexity while maintaining measurement precision
Solution Approach 2:
The patent uses a codec (a standardized compression/decompression system) to perform the function previously requiring a specialized noise removal apparatus. The codec's coding characteristics are used to define the likelihood of the input signal being a predetermined type, effectively copying the essential functionality of the noise removal apparatus through a more general, less complex system
2Device complexity
If coding techniques are used to define likelihood without a noise removal apparatus, then the device complexity is reduced, but achieving accurate signal reconstruction becomes more difficult
Solution Approach 1:
The patent changes the parameter used to define signal likelihood from traditional noise removal metrics to coding characteristics (such as compression ratio, bit rate, or other codec-specific parameters). By using these alternative parameters that are naturally produced during the coding process, the invention achieves accurate signal reconstruction without requiring complex noise removal apparatus, thus maintaining manufacturing precision while reducing device complexity
3Ease of operation
If the observation process matrix is singular, then the reconstruction problem becomes ill-posed and cannot be uniquely solved, but adding regularization terms increases the complexity of the optimization problem
Solution Approach 1:
The patent performs preliminary action by defining the likelihood of the input signal being a predetermined type before solving the optimization problem. By using coding characteristics to establish prior knowledge about the signal type in advance, the invention transforms the ill-posed problem into a well-posed one, making the reconstruction solvable without significantly increasing the complexity of the optimization process itself
Data Source
AI summary
Provided is a signal reconstruction method executed by a signal reconstruction apparatus including a processor and a memory that stores a codec. The signal reconstruction method includes reconstructing an input signal according to a desired purpose, and in the reconstructing, a likelihood of the input signal being a predetermined type of signal is considered by executing coding on a processing result of the input signal, based on the codec previously determined according to a type of the input signal.