Bayesian Filter Design for Computational Medicine : A State-Space Estimation Framework /

This book serves as a tutorial that explains how different state estimators (Bayesian filters) can be built when all or part of the observations are binary. The book begins by briefly motivating the need for point process state estimation followed by an introduction to the overall approach, as well...

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Bibliographic Details
Main Authors:	Wickramasuriya, Dilranjan S. (Author), Faghih, Rose T. (Author)
Corporate Author:	SpringerLink (Online service)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2024.
Edition:	1st ed. 2024.
Subjects:	Computational neuroscience. Neurotechnology (Bioengineering). Biomedical engineering. Signal processing. Biophysics. Cell interaction. Computational Neuroscience. Neuroengineering. Biomedical Engineering and Bioengineering. Digital and Analog Signal Processing. Mechanobiological Cell Signaling. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Introduction
Some Useful Statistical Results
State-space Model with One Binary Observation
State-space Model with One Binary and One Continuous Observation
State-space Model with One Binary and Two Continuous Observations
State-space Model with One Binary, Two Continuous and a Spiking-type Observation
State-space Model with One Marked Point Process (MPP) Observation
Additional Models and Derivations
MATLAB Code Examples
List of Supplementary MATLAB Functions.