TAILIEUCHUNG - Sabatier Agrawal Machado Advances in Fractional Calculus Episode 9

Tham khảo tài liệu 'sabatier agrawal machado advances in fractional calculus episode 9', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | A FRACTIONAL CALCULUS PERSPECTIVE 307 Following this line of research and looking for better performance GAs this paper proposes a GA for the design of combinational logic circuits using fractional-order dynamic fitness functions. The area of fractional calculus FC deals with the operators of integration and differentiation to an arbitrary including noninteger order and is as old as the theory of classical differential calculus 4 5 . The theory of FC is a well-adapted tool to the modelling of many physical phenomena allowing the description to take into account some peculiarities that classical integer-order models simply neglect. Nevertheless the application of FC has been scarce until recently but the advances on the theory of chaos motivated a renewed interest in this field. In the last two decades we can mention research on viscoelasticity damping chaos fractals biology signal processing system identification diffusion and wave propagation electromagnetism and automatic control 6 7 20 8 . Bearing these ideas in mind the article is organized as follows. Section 2 describes the adopted GA as well as the fractional-order dynamic fitness functions. Section 3 presents the simulation results and finally section 4 outlines the main conclusions and addresses perspectives towards future developments. 2 The Adopted Genetic Algorithm In this section we present the GA in terms of the circuit encoding as a chromosome the genetic operators and the static and dynamic fitness functions. Problem definition The circuits are specified by a truth table with input bits ordered according with the Gray code. The goal is to implement a functional circuit with the least possible complexity. Two sets of logic gates have been defined as shown in Table 1 being Gset a the simplest one . a RISC-like set and Gset b a more complex gate set . a CISC-like set . For each gate set the GA searches the solution space based on a simulated evolution aiming the survival of the fittest .

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