Nonlinear dynamic modeling of physiological systems /

Nonlinear dynamic modeling of physiological systems /

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Bibliographic Details
Author / Creator:Marmarelis, Vasilis Z.
Imprint:Hoboken, N.J. : Wiley-Interscience, c2004.
Description:1 online resource (xvi, 541 p.) : ill.
Language:English
Series:IEEE Press series on biomedical engineering
IEEE Press series in biomedical engineering.
Subject:
Physiology -- Mathematical models.
Nonlinear theories.
Nonlinear Dynamics.
Physiology.
Nonlinear theories.
Physiology -- Mathematical models.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/8680531
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Other authors / contributors:IEEE Engineering in Medicine and Biology Society.
ISBN:9780471679370
0471679372
0471469602
9780471469605
Notes:"IEEE Engineering in Medicine and Biology Society, sponsor."
Includes bibliographical references (p. 507-533) and index.
Table of Contents:
  • Prologue
  • 1. Introduction
  • 1.1. Purpose of this Book
  • 1.2. Advocated Approach
  • 1.3. The Problem of System Modeling in Physiology
  • 1.4. Types of Nonlinear Models of Physiological Systems
  • 2. Nonparametric Modeling
  • 2.1. Volterra Models
  • 2.2. Wiener Models
  • 2.3. Efficient Volterra Kernel Estimation
  • 2.4. Analysis of Estimation Errors
  • 3. Parametric Modeling
  • 3.1. Basic Parametric Model Forms and Estimation Procedures
  • 3.2. Volterra Kernels of Nonlinear Differential Equations
  • 3.3. Discrete-Time Volterra Kernels of NARMAX Models
  • 3.4. From Volterra Kernel Measurements to Parametric Models
  • 3.5. Equivalence Between Continuous and Discrete Parametric Models
  • 4. Modular and Connectionist Modeling
  • 4.1. Modular Form of Nonparametric Models
  • 4.2. Connectionist Models
  • 4.3. The Laguerre-Volterra Network
  • 4.4. The VWM Model
  • 5. A Practitioner's Guide
  • 5.1. Practical Considerations and Experimental Requirements
  • 5.2. Preliminary Tests and Data Preparation
  • 5.3. Model Specification and Estimation
  • 5.4. Model Validation and Interpretation
  • 5.5. Outline of Step-by-Step Procedure
  • 6. Selected Applications
  • 6.1. Neurosensory Systems
  • 6.2. Cardiovascular System
  • 6.3. Renal System
  • 6.4. Metabolic-Endocrine System
  • 7. Modeling of Multiinput/Multioutput Systems
  • 7.1. The Two-Input Case
  • 7.2. Applications of Two-Input Modeling to Physiological Systems
  • 7.3. The Multiinput Case
  • 7.4. Spatiotemporal and Spectrotemporal Modeling
  • 8. Modeling of Neuronal Systems
  • 8.1. A General Model of Membrane and Synaptic Dynamics
  • 8.2. Functional Integration in the Single Neuron
  • 8.3. Neuronal Systems with Point-Process Inputs
  • 8.4. Modeling of Neuronal Ensembles
  • 9. Modeling of Nonstationary Systems
  • 9.1. Quasistationary and Recursive Tracking Methods
  • 9.2. Kernel Expansion Method
  • 9.3. Network-Based Methods
  • 9.4. Applications to Nonstationary Physiological Systems
  • 10. Modeling of Closed-Loop Systems
  • 10.1. Autoregressive Form of Closed-Loop Model
  • 10.2. Network Model Form of Closed-Loop Systems
  • Appendix I. Function Expansions
  • Appendix II. Gaussian White Noise
  • Appendix III. Construction of the Wiener Series
  • Appendix IV. Stationarity, Ergodicity, and Autocorrelation Functions of Random Processes
  • References
  • Index

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