Scientists have developed an exact approach to a key quantum error correction problem once believed to be unsolvable, and have shown that what appeared to be hardware-related errors may in fact be due ...

Previous TCAM-based RegEx matching algorithms a priori assume that a deterministic finite automaton (DFA) can be built for a given set of RegEx patterns. However, practical RegEx patterns contain ...

Ultimately, the new approach works because of how it encodes information. Classical computers use bits, which can take one of ...

Learning automata constitute a branch of reinforcement learning that enables algorithms to iteratively refine their actions through continual interaction with uncertain, or stochastic, environments.

Multivariate cryptography and finite field algorithms are two interlocking research areas that underpin many modern cryptographic systems and computational methods. Multivariate cryptography ...

The novelty of the model is the use of dynamic and interpretable feature engineering framework comprising of two innovations: 1) Flower Automata Pattern (FAP) for self-organized pattern-based feature ...

In addition, attention must be placed on temporal datasets that analyze crucial information about the timing of pattern occurrences and stream datasets to manage high-speed streaming data. Several ...

It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both ...

RustyLR is a parser generator that converts context-free grammars into IELR(1)/LALR(1) tables with deterministic LR and GLR parsing strategies. It supports custom reduce action in Rust, with beautiful ...

We discuss the cellular automata approach and its extensions, the lattice Boltzmann and multiparticle methods. The potential of these techniques is demonstrated in the case of modeling complex systems ...