Bayesian Signal Analysis for Reliable Peak Detection in Noise

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Solution Overview

Problem

Existing analysis methods are susceptible to variations in measurement data, leading to unreliable results, particularly in high-noise environments.

Innovation Solution

An analysis method utilizing Bayesian inference to model measurement data, incorporating both signal and noise components, enabling estimation of probability distributions for peak positions and quantitative values.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If regression analysis or least squares method is used to analyze measurement data, then the analysis process is simple and fast, but the reliability of analysis results is degraded due to variations in measurement data and noise

Engineering Contradiction:

Improvereliability of analysis resultsVSAvoidcomplexity of analysis method

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent changes the fundamental parameter of the analysis approach by transitioning from deterministic regression analysis to probabilistic Bayesian inference. This involves changing how parameters are treated - from fixed values to probability distributions - allowing the system to account for measurement variations and noise while maintaining analytical rigor

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent introduces probability distributions as an intermediary layer between the raw measurement data and the final analysis results. By modeling both signal and noise components through probability distributions and using Bayesian inference as the mediating process, the system reliably separates true signals from noise while quantifying uncertainty

Inventive Principle:

Principle #24Intermediary (Mediator)

2Object-affected harmful factors

If conventional analysis methods are used, then the analysis process is straightforward, but the ability to handle high-noise environments is insufficient

Engineering Contradiction:

Improveimpact of noise on analysisVSAvoidprecision of measurement data

Core Design Contradiction:

Object-affected harmful factorsVSMeasurement precision

Solution Approach 1:

The patent segments the measurement data into distinct components - signal portions and noise portions - by modeling them separately with different probability distributions. This segmentation allows the analysis to treat each component appropriately, improving the system's ability to handle noisy environments while maintaining measurement precision

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent converts the harmful effect of noise into a beneficial feature by explicitly modeling noise as a probability distribution component. Instead of treating noise as an unwanted disturbance to be eliminated, the invention incorporates it into the analysis framework, allowing for more robust and reliable results in high-noise environments

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Data Source

PatentUS12530428B2Analysis method and diagnosis assistance method

Publication Date: 2026.01.20 SHIMADZU CORP

AI summary

An analysis method for analyzing a sample includes a first step of acquiring measurement data including a first signal based on the sample and a second signal based on noise added to the first signal as a result of analysis of the sample, a second step of assuming a shape representing the first signal and a shape representing the second signal and modeling the measurement data using Bayesian inference, and a third step of estimating a probability distribution of characteristics of the sample based on the modeled measurement data.