Results 81 to 90 of about 185,534 (230)
Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh +3 more
wiley +1 more source
The approach of physical in materia computing incorporates parallel computing within the medium itself. A scalable and energy‐efficient, oxide‐based computational platform is realized in form of a nanoporous network of volatile niobium oxide memristors sandwiched between top and bottom metallic electrodes, and then tested for prediction and ...
Joshua Donald +7 more
wiley +1 more source
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad +4 more
wiley +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Asset pricing in a Lucas "fruit-tree' economy with non-additive beliefs [PDF]
We study a Lucas (1978) "fruit-tree" economy under the assumption that agents are Choquet expected utility (CEU) rather than standard expected utility (EU) decision makers.
Alexander Zimper
core +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
The History of Macroeconomics from Keynes’s General Theory to the Present [PDF]
This paper is a contribution to the forthcoming Edward Elgar Handbook of the History of Economic Analysis volume edited by Gilbert Faccarello and Heinz Kurz.
Michel DE VROEY, Pierre MALGRANGE
core
Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin +4 more
wiley +1 more source
Microfoundations: a decisive dividing line between Keynesian and new classical macroeconomics? [PDF]
It is often argued that what marks the difference between Keynesian macroeconomics and new classical macroeconomics (the first installment of dynamic stochastic general equilibrium models) is the presence of microfoundations.
Michel DE VROEY
core
Macroeconometric Modelling with a Global Perspective [PDF]
This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic ...
M. Hashem Pesaran, Ron P. Smith
core

