Digital Signal Stabilization Using Boundary Coefficients
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Solution Overview
Problem
Ambient light sensors experience fluctuations in light intensity readings, leading users to mistakenly attribute these fluctuations to noise, which questions the noise-filtering capability of the sensors, especially in low ambient light and noise environments.
Innovation Solution
A method is introduced to stabilize digital signals by setting boundary coefficients and correction coefficients, updating a center value based on differences between successive data readings, and outputting either the center value or updated center value depending on these coefficients, thereby improving signal stability and minimizing fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If digital signal data is directly output without stabilization, then the response speed is fast, but the output signal fluctuates significantly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing boundary coefficients before signal processing. These coefficients are used to predict and prevent fluctuations before they occur in the output signal, rather than reacting to them after they appear. The center value is continuously updated based on historical data to proactively stabilize future outputs.
Solution Approach 2:
The patent implements feedback by continuously comparing the difference between consecutive signal values against predetermined boundary coefficients. When the difference exceeds the boundary, the center value is updated to the new signal value, creating a closed-loop control system that automatically adjusts to maintain signal stability within acceptable ranges.
2Stability of the object's composition
If a stabilization method with boundary coefficients is applied, then the output signal stability is improved, but the computational complexity increases
Solution Approach 1:
The patent segments the complex signal stabilization problem into simple, discrete operations: calculating the difference between consecutive values, comparing against a boundary coefficient, and conditionally updating the center value. This segmentation transforms a potentially complex filtering algorithm into a series of simple arithmetic and logical operations that are computationally efficient.
Solution Approach 2:
The patent uses parameter changes by dynamically adjusting the center value based on the signal difference and boundary coefficients. Instead of complex real-time calculations, the system changes the parameter (center value) discretely when specific conditions are met, reducing computational burden while maintaining stabilization effectiveness.
3Stability of the object's composition
If the boundary coefficient is set strictly, then the signal fluctuation is minimized, but the signal-to-noise ratio deteriorates
Solution Approach 1:
The patent applies dynamics by making the boundary coefficient adjustable rather than fixed. The system can adapt the boundary coefficient based on signal characteristics and environmental conditions, allowing it to be strict when needed for fluctuation control and lenient when signal-to-noise ratio is more critical. This dynamic adjustment resolves the contradiction between fluctuation minimization and noise preservation.
Solution Approach 2:
The patent changes the parameter (boundary coefficient) based on signal conditions. When signal fluctuations are problematic, the boundary coefficient can be reduced for stricter control. When signal-to-noise ratio is more important, the boundary coefficient can be increased to allow more variation. This parameter adaptation allows the system to optimize for different operational requirements.
Data Source
AI summary
A method of stabilizing data of digital signals is provided. The method includes steps of: setting a boundary coefficient; reading a piece of digital data; defining a value of the piece of digital data as a center value; outputting the value of the piece of digital data; reading a next piece of digital data; subtracting a value of the next piece of digital data from the previously outputted value to obtain a positive difference or a negative difference; and determining whether or not an absolute value of the positive or negative difference is larger than the boundary coefficient, if not, outputting the center value, if yes, updating the center value such that the updated center value is equal to the value of the next piece of digital data, and outputting the updated center value.