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Static memory optimization by clustering and neural networks in embedded devices

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Published:16 June 2011Publication History

ABSTRACT

In every network bus there is a situation of an output signal calculated on the base of few input signals. This is implemented by function, written on program language. When entire program is realized it will be written in flash memory of the controller that transmits the signals.

In many cases output signal values are formed in clusters, groups with same output value and close input values. In present investigation different methods of approaches are engaged and their positive and negative sides are compared. Algorithms for founding boundaries of such clusters using polynomials are suggested in the paper. Methods for their realizations by functions with minimal usage of memory (flash and RAM) are suggested. Neural networks are also investigated in such direction.

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  1. Static memory optimization by clustering and neural networks in embedded devices

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                        CompSysTech '11: Proceedings of the 12th International Conference on Computer Systems and Technologies
                        June 2011
                        688 pages
                        ISBN:9781450309172
                        DOI:10.1145/2023607

                        Copyright © 2011 ACM

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                        Association for Computing Machinery

                        New York, NY, United States

                        Publication History

                        • Published: 16 June 2011

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