Results 61 to 70 of about 26,341 (261)
On canalizing Boolean functions [PDF]
Boolean networks are an important model of gene regulatory networks in systems and computational biology. Such networks have been widely studied with respect to their stability and error tolerance. It has turned out that canalizing Boolean functions and their subclass, the nested canalizing functions, appear frequently in such networks.
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Self-Predicting Boolean Functions [PDF]
A Boolean function $g$ is said to be an optimal predictor for another Boolean function $f$, if it minimizes the probability that $f(X^{n})\neq g(Y^{n})$ among all functions, where $X^{n}$ is uniform over the Hamming cube and $Y^{n}$ is obtained from $X^{n}$ by independently flipping each coordinate with probability $δ$.
Weinberger, Nir, Shayevitz, Ofer
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Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
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Transformations of Boolean Functions.
Boolean functions are characterized by the unique structure of their solution space. Some properties of the solution space, such as the possible existence of a solution, are well sought after but difficult to obtain. To better reason about such properties, we define transformations as functions that change one Boolean function to another while ...
Jeffrey M. Dudek, Dror Fried
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Strain‐Modulated Reconfigurable Optical Information Processing in Flexible Graphene/PDMS
Graphene/PDMS—a stable, mechanically robust, and highly tunable flexible composite, exhibits excellent strain‐tunability. The spatial self‐phase modulation (SSPM) effect can be reversibly and continuously modulated by strain. A strain‐gated optical switch can be constructed, thereby realizing reconfigurable optical logic gates and reversible switching ...
Zexin Cui +13 more
wiley +1 more source
The Complexity of the Representation of Multiple-Output Boolean Functions
This paper considers cost of logic circuits that implement Boolean functions. The realization of Boolean functions is considered in the class of reversible logic circuits.
S. Vinokurov, A. Frantseva
doaj
We report the solid‐state ball milling, a traditional, reliable, mass‐productive material processing, to prepare the air‐stable and dual‐phase GeSe2‐x nanoparticles with extended photodetection feasibility toward optical‐wavelength regions. We further display photonic multi‐valued logic (MVL) circuit through the employment of a hybrid PMMA/GeSe2‐x ...
An‐Ting Tsai +8 more
wiley +1 more source
Here Boolean functions are considered as functions from an \(n\)-dimensional vector space over a 2-element field to the field. A Boolean function is normal if and only if it is constant on an affine subspace of dimension \([n/2]\). This paper gives some characterizations of normality and relationships with other classes such as resilient functions ...
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A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Symmetry groups of boolean functions
We prove that every abelian permutation group, but known exceptions, is the symmetry group of a boolean function. This solves the problem posed in the book by Clote and Kranakis. In fact, our result is proved for a larger class of groups, namely, for all groups contained in direct sums of regular groups.
Mariusz Grech, Andrzej Kisielewicz 0001
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