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CHAPTER
                                                                   2




                             Dynamic Neural Networks: Structures

                                              and Training Methods







                                2.1 ARTIFICIAL NEURAL                    To generate any model, we need to have at
                                  NETWORK STRUCTURES                   our disposal:
                                                                       • a basis, i.e., a set of elements from which mod-
                          2.1.1 Generative Approach to Artificial         els are formed;
                                Neural Network Design                  • the rules used to form models by appropri-
                                                                         ately combining the elements of the basis:
                          2.1.1.1 The Structure of the Generative        • rules for the structuring of models;
                                 Approach
                                                                         • rules for parametric adjustment of gener-
                            The generative approach is widely used in       ated models.
                          applied and computational mathematics. This                                         1
                                                                         One of the generative approach variants is
                          approach, extended by the ideas of ANN mod-
                                                                       that the desired dependence y(x) is represented
                          eling, is very promising as a flexible tool for the  as a linear combination of the basis functions
                          formation of dynamical system models.        ϕ i (x), i = 1,...,n, i.e.,
                            The generative approach is interpreted fur-
                                                                                         n
                          ther as follows. We can treat the class of models
                                                                           y(x) = ϕ 0 (x) +  λ i ϕ i (x), λ i ∈ R.  (2.1)
                          which contains the desired (generated) dynami-
                                                                                        i=1
                          cal system model as a collection of tools produc-
                          ing dynamical system models that satisfy some  The set of functions {ϕ i (x)},i = 1,...,n, we will
                          specified requirements. There are two main re-  call the functional basis (FB). The expression of
                          quirements for this set of tools. Firstly, it must  the form (2.1) is a decomposition (expansion) of
                          generate a potentially rich class of models (i.e., it  the function y(x) with respect to the functional
                                                                                  n
                          must provide extensive choice possibilities) and,  basis {ϕ i (x)} i=1 .
                                                                         We will further consider the generation of the
                          secondly, it should have as many as possible
                          simple “arrangement,” so that the implementa-  FB expansion by varying the adjustable parame-
                                                                       ters (the coefficients λ i in the expansion (2.1)) as
                          tion of this class of models is not an “unbear-
                          able” problem. These two requirements, gener-
                                                                       1 Examples of other variants are generative grammars from
                          ally speaking, are mutually exclusive. How and
                                                                       the theory of formal grammars and languages [1–3], a syn-
                          by what tools to ensure an acceptable balance  tactic approach to the description of patterns in the theory of
                          between them is discussed later in this section.  pattern recognition [4–7].

                          Neural Network Modeling and Identification of Dynamical Systems
                          https://doi.org/10.1016/B978-0-12-815254-6.00012-5  35        Copyright © 2019 Elsevier Inc. All rights reserved.
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