Variable Sample Rate Waveform Histogram Generation
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Solution Overview
Problem
Existing methods for generating histogram data from sampled waveforms fail to accurately account for values between sampled data points, leading to significant inaccuracy, especially with continuous waveforms and analog to digital converter quantization levels.
Innovation Solution
The method involves generating lines between consecutive sampled data points and applying linear interpolation to determine the time each line spends within bins, accumulating this time for each bin to generate more accurate histogram data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If simple counting of sampled data points is used to generate histogram data, then the method is computationally simple and fast, but the histogram data accuracy deteriorates significantly for continuous waveforms
Solution Approach 1:
The patent segments the continuous waveform into multiple linear segments between consecutive sampled data points. Each segment is analyzed individually to determine the time spent in each bin, allowing for accurate representation of the continuous waveform while maintaining computational efficiency through systematic processing of discrete segments.
Solution Approach 2:
The patent performs preliminary linear interpolation between sampled data points to estimate waveform values at intermediate time points before generating the histogram. This preliminary action allows the algorithm to account for the continuous nature of the waveform without requiring exhaustive sampling of every possible point.
2Measurement precision
If linear interpolation is applied between sampled data points to determine time spent in bins, then the histogram data accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent divides the waveform analysis into discrete segments between sampled points, applying linear interpolation only where necessary. This segmentation allows the algorithm to balance accuracy with computational efficiency by avoiding unnecessary calculations in regions where simple counting suffices.
Solution Approach 2:
The patent applies linear interpolation selectively rather than universally - only between consecutive sampled data points where the waveform may cross bin boundaries. This partial application of the more complex method maintains accuracy where needed while avoiding excessive computational overhead in regions where simpler methods suffice.
3Measurement precision
If more sampled data points are collected to improve histogram accuracy, then the representation of continuous waveforms improves, but the data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary linear interpolation to predict waveform behavior between sampled points, allowing accurate histogram generation without requiring additional sampled data points. This preliminary estimation of intermediate values achieves better waveform representation while maintaining the original sampling rate and processing time.
Solution Approach 2:
The patent creates a virtual representation of the continuous waveform through linear interpolation between sampled points, effectively copying the essential characteristics of the continuous signal without physically acquiring additional data points. This virtual copying achieves improved accuracy without the time cost of actual additional sampling.
Data Source
AI summary
A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining an array of bins, each bin identified by a unique number and including histogram data for a range of y values; for each consecutive pair of data points including a current data point and a next data point, determining a corresponding one of a plurality of linear equations, each linear equation defining a line between the current data point and the next data point; for each line, determining an amount of time that the y value of the line is within the range of values for each bin from the current data point to the next data point; and adding the time to the histogram data for each bin.