Results 71 to 80 of about 2,786,322 (296)
Advanced Robotics Research, EarlyView.DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano +3 more
wiley +1 more source
Analysis of affine equivalent boolean functions for cryptography [PDF]
, 2003 Boolean functions are an important area of study for cryptography. These functions, consisting merely of one's and zero's, are the heart of numerous cryptographic systems and their ability to provide secure communication.
Fuller, Joanne Elizabeth
core
Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Advanced Science, EarlyView.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
wiley +1 more source
Complexity Lower Bound for Boolean Functions in the Class of Extended Operator Forms
Известия Иркутского государственного университета: Серия "Математика", 2019 Starting with the fundamental work of D.E.Muller in 1954, the polynomial representations of Boolean functions are widely investigated in connection with the theory of coding and for the synthesis of circuits of digital devices.
A.S. Baliuk
doaj +1 more source
On Circuit Functionality in Boolean Networks
Bulletin of Mathematical Biology, 2013 It has been proved, for several classes of continuous and discrete dynamical systems, that the presence of a positive (resp. negative) circuit in the interaction graph of a system is a necessary condition for the presence of multiple stable states (resp. a cyclic attractor). A positive (resp.
Comet, Jean-Paul +9 more
openaire +10 more sources
Self-Predicting Boolean Functions [PDF]
SIAM Journal on Discrete Mathematics, 2018 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
openaire +4 more sources
Evolving boolean functions satisfying multiple criteria
, 2002 Many desirable properties have been identified for Boolean functions with cryptographic applications. Obtaining optimal tradeoffs among such properties is hard.
Subhamoy Maitra +14 more
core +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
Advanced Science, EarlyView.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
Transformations of Boolean Functions.
, 2019 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
openaire +3 more sources
Integration of Reconfigurable p‐Bit and 1R Crossbar Array for Memristive Probabilistic Computing
Advanced Science, EarlyView.A memristive probabilistic computing system is demonstrated by integrating stochastic p‐bits based on volatile memristors with a 1R crossbar array encoding interaction weights. The system performs weighted‐sum operations across the array and updates p‐bits iteratively.
Keunho Soh +7 more
wiley +1 more source