Results 191 to 200 of about 2,393,674 (352)

Fuzzy temporal logic based railway passenger flow forecast model. [PDF]

Comput Intell Neurosci, 2014
Dou F, Jia L, Wang L, Xu J, Huang Y.
europepmc   +1 more source

RRAM Variability Harvesting for CIM‐Integrated TRNG

Advanced Electronic Materials, EarlyView.
This work demonstrates a compute‐in‐memory‐compatible true random number generator that harvests intrinsic cycle‐to‐cycle variability from a 1T1R RRAM array. Parallel entropy extraction enables high‐throughput bit generation without dedicated circuits. This approach achieves NIST‐compliant randomness and low per‐bit energy, offering a scalable hardware
Ankit Bende, Gokulnath Rajendran, Regina Dittmann, Anupam Chattopadhyay, Vikas Rana   +4 more
wiley   +1 more source

Reversible and Controllable Transition Between Filamentary and Interfacial Resistive Switching in HfO2‐Based Memristors

Advanced Electronic Materials, EarlyView.
5 nm HfO2 memristors exhibit a fully reversible, voltage‐controlled transition between filamentary and interfacial switching within the same device. At high voltages, a filament forms and dominates the conduction, whereas at lower voltages the device reversibly returns to interfacial mode without defect accumulation, implying a new reversible ...
Cuo Wu, Hao Shen, Richard Schroedter, Chong Peng, Hampus Hoffman, Stefan Slesazeck, Ronald Tetzlaff, Thomas Mikolajick, Benjamin Max   +8 more
wiley   +1 more source

(To Appear) The LTL Whisperer: Prompting AI to Explain Temporal Logic: Supplemental Information

Sonora Halili, Paola Spoletini, Alicia M. Grubb   +2 more
openalex   +1 more source

Reconfigurable, Non‐Volatile Switching in WO3 Film for Resistive Memory and Multistate Programming Toward Energy‐Efficient Neuromorphic Computing Applications

Advanced Electronic Materials, EarlyView.
WO3${\rm WO}_3$ based resistive switching device was precisely controlled and shows the reconfigurable, non‐volatile switching which can be programmable to multi‐resistance states for memory applications. The memory device can also be utilised for low energy neuromorphic application.
Keval Hadiyal, Nagarajan Raghavan, Ramesh Mohan Thamankar   +2 more
wiley   +1 more source

The Influence of Jerzy Łoś on Early Developments in Temporal Logic

, 2021
Aleksander Parol
openalex   +2 more sources

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kimh, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Multi-agent reinforcement learning with synchronized and decomposed reward automaton synthesized from reactive temporal logic [PDF]

Chenyang Zhu, Jinyu Zhu, Wen Si, Xueyuan Wang, Fang Wang   +4 more
openalex   +1 more source

Maximum Realizability for Linear Temporal Logic Specifications [PDF]

, 2018
Rayna Dimitrova, Mahsa Ghasemi, Ufuk Topcu   +2 more
openalex   +1 more source

Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Advanced Energy and Sustainability Research, EarlyView.
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar, Arunkumar Chandrasekhar, Poongundran Selvaprabhu   +2 more
wiley   +1 more source