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Unstable periodic orbits and noise in chaos computing
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Image of FIG. 1.
FIG. 1.

Schematic of chaotic computing model. Inputs are mapped to an initial condition of the chaotic system working as a computing engine, and the final state of the chaotic system is decoded to output.

Image of FIG. 2.
FIG. 2.

(Color online) Chua circuit-based logic block (Ref. 19).

Image of FIG. 3.
FIG. 3.

(Color online) Statistical measures, mean and variance, of the error in estimating robustness of different instructions against noise. The error is the difference between the estimated SNR and the experimental SNR for each instruction. The mean of these errors at each iteration is reported in the left panel, and the variance of the error at each iteration is presented in right panel. The solid lines denote cases where, for (p − 1) iterations of the map, period p UPOs are used for modeling. Dashed lines denote the means and variances when period-7 UPOs are used for predicting the SNR. Dotted lines show the means and variances of the difference r, where linearization is performed along each orbit.


Generic image for table
Table I.

Instruction set of the logistic map for different iteration numbers obtained from a time series.

Generic image for table
Table II.

Truth table of a typical two input, one output function.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Unstable periodic orbits and noise in chaos computing