UID:
edoccha_9959238932602883
Format:
1 online resource (xxiv, 564 pages) :
,
illustrations (some color).
Edition:
Second edition.
ISBN:
0-12-409525-9
Series Statement:
Elsevier insights
Content:
Modelling Methodology for Physiology and Medicine, Second Edition, offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modeling methodology that is widely applicable to physiology and medicine.
Note:
Description based upon print version of record.
,
Front Cover; Modelling Methodology for Physiology and Medicine; Copyright Page; Contents; Preface; Preface to the Second Edition; List of Contributors; 1 An Introduction to Modelling Methodology; 1.1 Introduction; 1.2 The Need for Models; 1.2.1 Physiological Complexity; 1.2.2 Models and Their Purposes; 1.3 Approaches to Modelling; 1.3.1 Modelling the Data; 1.3.2 Modelling the System; 1.4 Simulation; 1.5 Model Identification; 1.5.1 A Framework for Identification; 1.5.2 Identification of Parametric Models; 1.5.3 Identification of Nonparametric Models; 1.6 Model Validation; Reference
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2 Control in Physiology and Medicine; 2.1 Introduction; 2.2 Modelling for Control System Design and Analysis; 2.2.1 Sets of Ordinary Differential Equations; 2.2.2 Linear State Space Models; 2.2.3 Transfer Functions; 2.2.3.1 Pole-Zero Cancellation; 2.2.3.2 Right-Half-Plane Zeros and Time Delays; 2.2.4 Discrete-Time State Space Models; 2.2.5 Discrete Auto-Regressive Models; 2.2.6 Step and Impulse Response Models; 2.2.7 System Identification; 2.3 Block Diagram Analysis; 2.3.1 Continuous-Time Block Diagram Analysis; 2.3.2 Discrete-Time Block Diagram Analysis
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2.4 Proportional-Integral-Derivative Control; 2.4.1 PID Tuning Techniques; 2.4.1.1 Ziegler-Nichols Closed-Loop Oscillations; 2.4.1.2 Frequency Response; 2.4.1.3 Cohen-Coon; 2.4.1.4 Internal Model Control-Based PID; 2.4.1.5 Ad hoc; 2.4.2 Discrete-Time PID; 2.5 Model Predictive Control; 2.6 Other Control Algorithms; 2.6.1 Fuzzy Logic; 2.6.2 Expert Systems; 2.6.3 Artificial Neural Networks; 2.6.4 On-Off; 2.7 Application Examples; 2.7.1 Type 1 Diabetes: Blood Glucose Control; 2.7.1.1 Models for Simulation; 2.7.1.2 Models for Control; 2.7.1.3 Control; 2.7.1.3.1 On-Off
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2.7.1.3.2 Proportional-Integral-Derivative (PID); 2.7.1.3.3 Model Predictive Control (MPC); 2.7.1.3.4 Fuzzy Logic; 2.7.2 Intensive Care Unit Blood Glucose Control; 2.7.2.1 Models; 2.7.2.2 Control; 2.7.3 Blood Pressure Control Using Continuous Drug Infusion; 2.7.3.1 Models; 2.7.3.2 Control; 2.7.4 Control of Anesthesia and Sedation; 2.7.4.1 Models; 2.7.4.2 Open-Loop Control; 2.7.4.3 Closed-Loop Control; 2.8 Summary; References; 3 Deconvolution; 3.1 Problem Statement; 3.2 Difficulty of the Deconvolution Problem; 3.2.1 Dealing with Physiological Systems
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3.2.2 A Classification of the Deconvolution Approaches; 3.3 The Regularization Method; 3.3.1 Deterministic Viewpoint; 3.3.1.1 The Choice of the Regularization Parameter; 3.3.1.2 The Virtual Grid; 3.3.1.3 Assessment of Confidence Limits; 3.3.2 Stochastic Viewpoint; 3.3.2.1 Confidence Limits; 3.3.2.2 Statistically Based Choice of the Regularization Parameter; 3.3.3 Numerical Aspects; 3.3.4 Constrained Deconvolution; 3.4 Other Deconvolution Methods; 3.5 Conclusions; References; 4 Structural Identifiability of Biological and Physiological Systems; 4.1 Introduction; 4.2 Background and Definitions
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4.2.1 The System
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English
Additional Edition:
ISBN 0-12-411557-8
Language:
English
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