Deterministic Component Identification via Spectrum Null Frequency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for evaluating electronic circuits and communication systems fail to accurately separate and measure the deterministic component from the probability density function, as they rely on accurate modeling of the deterministic component, which is often uncertain, especially when dealing with trapezoidal distributions.
Innovation Solution
A deterministic component identifying apparatus that calculates the standard deviation, spectrum, and null frequency of the probability density function to determine the distribution shape and ratio of the deterministic component, allowing for accurate separation of deterministic and random components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the deterministic component is calculated based on the first null frequency in the spectrum of the probability density function, then the calculation can be performed, but the accuracy deteriorates unless an accurate model is determined for the deterministic component
Solution Approach 1:
The invention changes the approach from determining complex distribution models to measuring specific parameters (standard deviation and trapezoid ratio) that directly characterize the deterministic component. By focusing on these key parameters rather than full model determination, the accuracy of deterministic component calculation is improved without the complexity of model selection and verification
Solution Approach 2:
The invention replaces the traditional spectral analysis method (which relies on identifying the first null frequency and assuming a model) with a new method based on calculating the standard deviation of the probability density function and measuring the trapezoid ratio. This substitution eliminates the need for model determination while maintaining calculation capability
2Reliability
If the deterministic component follows a trapezoidal distribution, then the distribution shape can be characterized, but the measurement precision deteriorates because the trapezoid ratio must be accurately measured
Solution Approach 1:
The invention performs preliminary calculation of the standard deviation of the probability density function before measuring the trapezoid ratio. This preliminary action provides a reference value that simplifies the subsequent trapezoid ratio measurement and reduces the precision requirements for the final ratio measurement
Solution Approach 2:
The invention segments the characterization of the deterministic component into two distinct measurement steps: first measuring the standard deviation (which captures the overall spread), then measuring the trapezoid ratio (which captures the shape). This segmentation allows each parameter to be measured with appropriate precision independently
Data Source
AI summary
A deterministic component identifying apparatus identifies a distribution shape of a deterministic component included in a probability density function supplied thereto. The apparatus includes a standard deviation calculating section that calculates a standard deviation of the probability density function, a spectrum calculating section that calculates a spectrum of the probability density function, a null frequency detecting section that detects a null frequency of the spectrum, and a ratio calculating section that calculates a ratio between a top portion and a bottom portion of a distribution of the deterministic component, based on the standard deviation of the probability density function and the null frequency of the spectrum.