Neural Source Localization Using Advanced Sensor Array Signal Processing Techniques

Abstract

This paper aims to describe a hybrid technique that combines the feasibility of our recently developed Multiresolution Analysis of Signal Subspace Invariance Technique (MASSIT) with the Finite Element Method (FEM) analytic model developed to obtain accurate localization scheme of neural sources in an extracellular recording environment. The power of the proposed method stems from the fact that robust array signal processing approach is fused with the FEM analysis yielding the closest scenario to practical experimental situations. Results from experimental signal and noise simulated composite are summarized and the overall performance is evaluated.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411595

Entities

People

  • D. J. Anderson
  • K. G. Oweiss

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Altitude
  • Arrays
  • Biomedical Engineering
  • Computations
  • Computer Science
  • Covariance
  • Data Acquisition
  • Data Science
  • Data Sets
  • Electrical Engineering
  • Engineering
  • Estimators
  • Experimental Data
  • Geometry
  • Signal Processing
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Computational Modeling and Simulation
  • Computer Vision.