Results 131 to 140 of about 13,297 (272)

Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

open access: yesAdvanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz   +4 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

open access: yesAdvanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj   +2 more
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

open access: yesAdvanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows   +7 more
wiley   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley   +1 more source

Engineering halogen-doped carbon dots for enhanced bioinspired synapses toward neuromorphic computing and neural interfaces. [PDF]

open access: yesMater Today Bio
Hao H   +10 more
europepmc   +1 more source

Scalable Platform Enabling Reservoir Computing With Nanoporous Oxide Memristors for Image Recognition and Time Series Prediction

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Hardware‐Based On‐Chip Learning Using a Ferroelectric AND‐Type Array With Random Synaptic Weights

open access: yesAdvanced Intelligent Systems, EarlyView.
This work demonstrates an energy‐efficient on‐chip learning system using an Metal‐Ferroelectric‐Insulator‐Semiconductor FeAND synaptic array. By employing a feedback alignment scheme with a separate backward array using fixed random weights, the system overcomes directional limitations of AND‐type arrays and achieves robust, low‐power learning suitable
Minsuk Song   +8 more
wiley   +1 more source

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