Paper
6 December 2001 Strange attractor in optical logic cells
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Abstract
Optical logic cells, employed in several tasks as optical computing or optically controlled switches for photonic switching, offer a very particular behavior when the working conditions are slightly modified. One of the more striking changes occurs when some delayed feedback is applied between one of the possible output gates and a control input. Some of these new phenomena have been studied by us and reported in previous papers. A chaotic behavior is one of the more characteristic results and its possible applications range from communications to cryptography. But the main problem related with this behavior is the binary character of the resulting signal. Most of the nowadays-employed techniques to analyze chaotic signals concern to analogue signals where algebraic equations are possible to obtain. There are no specific tools to study digital chaotic signals. Some methods have been proposed. One of the more used is equivalent to the phase diagram in analogue chaos. The binary signal is converted to hexadecimal and then analyzed. We represented the fractal characteristics of the signal. It has the characteristics of a strange attractor and gives more information than the obtained from previous methods. A phase diagram, as the one obtained by previous techniques, may fully cover its surface with the trajectories and almost no information may be obtained from it. Now, this new method offers the evolution around just a certain area being this lines the strange attractor.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ana P. Gonzalez-Marcos and Jose Antonio Martin-Pereda "Strange attractor in optical logic cells", Proc. SPIE 4470, Photonic Devices and Algorithms for Computing III, (6 December 2001); https://doi.org/10.1117/12.449669
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Cited by 1 scholarly publication.
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KEYWORDS
Fractal analysis

Binary data

Chaos

Analog electronics

Optical logic

Logic

Signal processing

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