Circuit Simulator Algorithmic Identity Eliminates Fourier Noise Floor
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Solution Overview
Problem
Circuit simulators introduce errors during Fourier analysis that create a noise floor, masking small signal components and limiting resolution, which existing methods cannot fully eliminate without compromising accuracy or increasing simulation time.
Innovation Solution
The simulator is made algorithmically identical to the Fourier analyzer over each Fourier analysis sample interval by ensuring a linear and time-invariant transformation, eliminating the noise floor caused by simulator errors while maintaining accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If circuit simulators perform Fourier analysis with standard error control, then simulation accuracy is maintained, but a noise floor is created that masks small signal components
Solution Approach 1:
The simulation interval is divided into multiple Fourier analysis sample intervals, with separate error control applied to each. This segmentation allows the simulator to maintain algorithmic consistency within each interval while reducing the overall noise floor through controlled error distribution across intervals.
Solution Approach 2:
The invention changes the error control parameters dynamically by adjusting the maximum error bound for each Fourier analysis sample interval. By setting appropriate error bounds that decrease with interval progression, the simulator achieves both low noise floor and high measurement precision without compromising simulation accuracy.
2Reliability
If simulator tolerances are tightened to reduce errors, then total error decreases, but the noise floor may increase
Solution Approach 1:
Different error control strategies are applied to different parts of the simulation. Within each Fourier analysis sample interval, the simulator uses consistent algorithmic choices with controlled error bounds, while allowing more flexibility between intervals. This local differentiation reduces noise floor without sacrificing overall simulation reliability.
3Productivity
If the simulator uses non-uniform time steps to adapt to circuit behavior, then simulation efficiency is improved, but algorithmic consistency with the Fourier analyzer is lost
Solution Approach 1:
The invention introduces dynamic error control that adapts to the circuit behavior while maintaining algorithmic consistency. The simulator can use non-uniform time steps for efficiency, but within each Fourier analysis sample interval, it ensures that the algorithmic choices remain consistent and the error bounds are controlled, thus maintaining both productivity and measurement precision.
4Measurement precision
If the simulator maintains strict algorithmic consistency to eliminate noise floor, then measurement precision improves, but device complexity increases
Solution Approach 1:
The invention extracts and separates the error control mechanism from the main simulation algorithm. By implementing a distinct error control system that operates independently alongside the standard simulation engine, the patent achieves noise floor elimination without significantly increasing the core simulator complexity. The error control module handles the consistency requirements while the main simulator remains unchanged.
Data Source
AI summary
A method for eliminating the Fourier analysis noise floor generated by a circuit simulator is disclosed. This is accomplished by making the simulator behavior during each Fourier analysis sample interval (704) algorithmically identical to that employed during every other sample interval. Thus between each Fourier analysis sample point (703), the step size, number of iterations, integration method, etc., are allowed to vary as needed with the proviso that each sample interval uses exactly the same sequence of time steps, and that each member of that sequence is algorithmically identical to the corresponding members in the sequences used on every other Fourier sample interval. In other words, the first time step in the first interval must be algorithmically identical to the first time step in every other interval. The same is true for the second step, the third step, and so on until the last step.