National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
EVOLUTIONARY DESIGN OF COMBINATIONAL DIGITAL CIRCUITS
Žák, Jan ; Hůlka, Tomáš (referee) ; Matoušek, Radomil (advisor)
This thesis focuses on the application of Cartesian Genetic Programming (CGP) for the design of combinational circuits. Within the scope of the work, CGP was implemented in Python using the NumPy library. The library was successfully tested on experimental tasks, the results of which are also discussed in the thesis.
Evolutionary Combinational Circuit Resynthesis
Pták, Ondřej ; Schwarz, Josef (referee) ; Sekanina, Lukáš (advisor)
This project deals with combinational digital circuits and their optimization. First there are presented main levels of abstraction utilized in the design of combinational digital circuits. Afterwards different methods are surveyed for optimization of combinational digital circuits. The next part of this project is mainly devoted to evolutionary algorithms, their common characteristics and branches: genetic algorithms, evolutionary strategies, evolutionary programming and genetic programming. The variant of genetic programming called Cartesian Genetic Programming (CGP) and the use of CGP in various areas, particularly in the synthesis and optimization of combinational logic circuits are described in detail. The project also discusses some modifications of CGP and the scalability problem of evolutionary circuit design. Consequential part of this thesis describes the method for evolution resynthesis of combinational digital circuits. There is description of design, especially the method of splitting circuits into subcircuits, and implementation details. Finally experiments with these method and their results are described.
Evolutionary Combinational Circuit Resynthesis
Pták, Ondřej ; Schwarz, Josef (referee) ; Sekanina, Lukáš (advisor)
This project deals with combinational digital circuits and their optimization. First there are presented main levels of abstraction utilized in the design of combinational digital circuits. Afterwards different methods are surveyed for optimization of combinational digital circuits. The next part of this project is mainly devoted to evolutionary algorithms, their common characteristics and branches: genetic algorithms, evolutionary strategies, evolutionary programming and genetic programming. The variant of genetic programming called Cartesian Genetic Programming (CGP) and the use of CGP in various areas, particularly in the synthesis and optimization of combinational logic circuits are described in detail. The project also discusses some modifications of CGP and the scalability problem of evolutionary circuit design. Consequential part of this thesis describes the method for evolution resynthesis of combinational digital circuits. There is description of design, especially the method of splitting circuits into subcircuits, and implementation details. Finally experiments with these method and their results are described.

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