B.Tech IV Year II Semester (R16)
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The problem of system modeling in Physiology: Types of Nonlinear models of physiological systems. Deductive and Inductive modeling. Nonparametric modeling: Volterra models. Wiener models. Efficient volterra kernel estimation Analysis of estimation errors.
Parametric modeling: Basic parametric model forms and Estimation procedures. Volterra kernels of nonlinear differential equations. Discrete-time volterra kernels of NARMAX models. From Volterra kernel measurements to parametric models. Equivalence between continuous and Discrete -parametric models.
Preliminary tests and Data preparation: Model specification and Estimation. Model validation and Interpretation. Outline of step-by-step procedure. Applications: Neurosensory systems: Cardiovascular system, Renal system, Metabolic- Endocrine system.
Modeling of multi input/multi output systems: The Two-input case. Application s of two- input modeling to physiological systems. The Multiinput case spatiotemporal and spectrotemporal modeling.
Modeling of neuronal systems: A General model of membrane and Synaptic dynamics, Functional integration in the Single neuron, Neuronal systems with Point process inputs Modeling of neuronal ensembles. Modeling of Closed-loop systems: Autoregressive form of Closed-loop model, Network model form of Closed-loop systems.
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