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Advanced Methods of Physiological System Modeling

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Cover of 'Advanced Methods of Physiological System Modeling'

Table of Contents

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    Book Overview
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    Chapter 1 Volterra-Wiener Analysis of a Class of Nonlinear Feedback Systems and Application to Sensory Biosystems
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    Chapter 2 Parameter Estimation for Nongaussian Processes via Second and Third Order Spectra with an Application to Some Endocrine Data
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    Chapter 3 Analysis of the Whole-Nerve Responses from the Exposed Auditory Nerve in Man to Pseudorandom Noise
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    Chapter 4 Nonlinear Models of Transduction and Adaptation in Locust Photoreceptors
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    Chapter 5 Identification of Intensive Nonlinearities in Cascade Models of Visual Cortex and its Relation to Cell Classification
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    Chapter 6 Modeling of Neuronal Networks Through Experimental Decomposition
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    Chapter 7 Theoretical Decomposition of Neuronal Networks
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    Chapter 8 The Geometry of System Identification: Fractal Dimension and Integration Formulae
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    Chapter 9 Fast Orthogonal Algorithms for Nonlinear System Identification and Time-Series Analysis
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    Chapter 10 New Algorithm for Korenberg-Billings Model of Nonlinear System Identification
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    Chapter 11 Nonlinear Filters for Tracking Chaos in Neurobiological Time Series
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    Chapter 12 Chaotic Heart Rate Dynamics in Isolated Perfused Rat Hearts
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    Chapter 13 Introduction to the Properties and Analysis of Fractal Objects, Processes, and Data
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    Chapter 14 Towards a Physics of Neocortex
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    Chapter 15 The Use of Wiener-Volterra Methods in the Analysis and Synthesis of Simulated Neural Networks
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    Chapter 16 Wiener Analysis of the Hodgkin-Huxley Equations
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Title
Advanced Methods of Physiological System Modeling
Published by
Springer US, December 2012
DOI 10.1007/978-1-4613-9789-2
ISBNs
978-1-4613-9791-5, 978-1-4613-9789-2
Editors

Marmarelis, Vasilis Z.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Student > Bachelor 1 33%
Researcher 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Agricultural and Biological Sciences 1 33%
Neuroscience 1 33%