Functional Decomposition – the Value and Implication for Both Neural Networks and Digital Designing
International Journal of Computational Intelligence and Applications
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General functional decomposition is mainly perceived as a logic synthesis method for implementing Boolean functions into FPGA-based architectures. However it also has important applications in many other fields of modern engineering and science.
In this paper, advantages of functional decomposition are demonstrated on "real life" examples. Application of decomposition-based methods in other fields of modern engineering is presented. In the case of decision tables, application of decomposition methods leads to significant benefits in the analysis process of data dependencies, especially in cases when the input decision tables are unmanageably large. Experimental results demonstrate that it can help implementing sequential machines using flip-flops or ROM memory. It also can be efficiently used as multilevel logic synthesis method for VLSI technology.
Computer algorithms; Decomposition method; Field programmable gate arrays; Integrated circuits—Very large scale integration; Neural networks (Computer science)
Computer Engineering | Controls and Control Theory | Digital Circuits | Electrical and Computer Engineering | Electrical and Electronics | Signal Processing | Systems and Communications | VLSI and Circuits, Embedded and Hardware Systems
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Functional Decomposition – the Value and Implication for Both Neural Networks and Digital Designing.
International Journal of Computational Intelligence and Applications, 6(1),