Results 131 to 140 of about 12,777 (302)

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

open access: yesAdvanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

A Compendium of Logic Gates Based on Reconfigurable Three‐Independent‐Gate Transistors Realized in FDSOI Hardware

open access: yesAdvanced Electronic Materials, EarlyView.
This work electrically characterizes sixteen logic gates built from three‐independent‐gate reconfigurable transistors fabricated on full‐scale 300 mm wafers using the industrial 22 nm fully depleted FDSOI process of GlobalFoundries. Static and time‐resolved measurements confirm correct operation, including a 1‐bit adder and reconfigurable AOI/OAI ...
Juan P. Martinez   +12 more
wiley   +1 more source

Coverage Path Planning Using Reinforcement Learning-Based TSP for hTetran—A Polyabolo-Inspired Self-Reconfigurable Tiling Robot [PDF]

open access: gold, 2021
Anh Vu Le   +4 more
openalex   +1 more source

Androgynous Fasteners for Robotic Structural Assembly [PDF]

open access: yes
We describe the design and analysis of an androgynous fastener for autonomous robotic assembly of high performance structures. The design of these fasteners aims to prioritize ease of assembly through simple actuation with large driver positioning ...
Cheung, Kenneth   +4 more
core   +1 more source

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

An iconic programming language for sensor-based robots [PDF]

open access: yes
In this paper we describe an iconic programming language called Onika for sensor-based robotic systems. Onika is both modular and reconfigurable and can be used with any system architecture and real-time operating system.
Gertz, Matthew   +2 more
core   +1 more source

Synchronization of Analog Neuron Circuits With Digital Memristive Synapses: An Hybrid Approach

open access: yesAdvanced Electronic Materials, EarlyView.
An hybrid circuit mimicking neural units coupled using memristive synapses is introduced. The analog neurons provide flexibility and robustness, and the digital memristive coupling guarantees the full reconfigurability of the interconnection. The onset of a synchronized spiking behavior in two circuits mimicking the Izhikevich neuron is discussed from ...
Lamberto Carnazza   +3 more
wiley   +1 more source

In‐Sensor Computing by Soft Threshold Logic Gates Under Different Humidity Conditions

open access: yesAdvanced Electronic Materials, EarlyView.
Soft nanocomposite materials, based on gold cluster‐assembled thin films implanted in polydimethylsiloxane substrate, can perform reliable processing in ambient environmental conditions. Humidity influences the resistive switching and computational capabilities of the nanocomposites, that can be used as multifunctional material combining sensing ...
Giacomo Nadalini   +2 more
wiley   +1 more source

Universal Reconfiguration of (Hyper-)cubic Robots

open access: yes, 2011
We study a simple reconfigurable robot model which has not been previously examined: cubic robots comprised of three-dimensional cubic modules which can slide across each other and rotate about each others' edges.
Abel, Zachary, Kominers, Scott D.
core  

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

open access: yesAdvanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez   +10 more
wiley   +1 more source

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