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Related Experiment Video

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Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice

Data Acquisition and Analysis In Brainstem Evoked Response Audiometry In Mice

Published on: May 10, 2019

Problem reduction representation for the linguistic analysis of waveforms.

G C Stockman¹, L N Kanal

¹SENIOR MEMBER, IEEE, Department of Computer Science, Michigan State University, East Lansing, MI 48824.

IEEE Transactions on Pattern Analysis and Machine Intelligence

|August 27, 2011

Summary

This study introduces a novel method for analyzing pattern data using a best-first search algorithm (SSS*) to match structural representations with sample data. This approach enables efficient, nondirectional structural analysis of complex patterns like carotid pulse waves.

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Area of Science:

Signal Processing
Pattern Recognition
Biomedical Engineering

Background:

Traditional pattern analysis often relies on sequential processing, limiting flexibility.
Nondirectional analysis is crucial for complex data structures where order is not strictly defined.

Purpose of the Study:

To present a novel algorithm for nondirectional structural analysis of pattern data.
To demonstrate the application of this algorithm in analyzing waveform data.

Main Methods:

Utilizing a problem reduction representation (PRR) of pattern structure.
Employing a best-first state space search algorithm (SSS*) for matching PRR with sample data.
Developing a waveform parsing system (WAPSYS) to implement the structural analysis paradigm.

Main Results:

The algorithm generates a tree structure representing recognized patterns and primitives.
The method allows for flexible, combined top-down and bottom-up tree construction.
Ambiguous matches are handled effectively using state space search with partial parse trees.

Conclusions:

The developed SSS*-based approach provides an effective method for nondirectional structural analysis.
WAPSYS successfully implemented this paradigm for analyzing complex waveform data, such as carotid pulse waves.