Results 61 to 70 of about 779,800 (277)

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Neural Networks: Implementations and Applications [PDF]

, 1996
Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in ...
Jain, L.C., Veelenturf, L.P.J., Vonk, E.
core   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Advancing Neural Networks: Innovations and Impacts on Energy Consumption

Advanced Electronic Materials
The energy efficiency of Artificial Intelligence (AI) systems is a crucial and actual issue that may have an important impact on an ecological, economic and technological level.
Alina Fedorova, Nikola Jovišić, Jordi Vallverdù, Silvia Battistoni, Miloš Jovičić, Milovan Medojević, Alexander Toschev, Evgeniia Alshanskaia, Max Talanov, Victor Erokhin   +9 more
doaj   +1 more source

Evolutionary optimization within an intelligent hybrid system for design integration [PDF]

, 1999
An intelligent hybrid approach has been developed to integrate various stages in total design, including formulation of product design specifications, conceptual design, detail design, and manufacture.
Su, D, Wakelam, M
core   +1 more source

Bio‐Inspired Molecular Events in Poly(Ionic Liquids)

Advanced Functional Materials, EarlyView.
Originating from dipolar and polar inter‐ and intra‐chain interactions of the building blocks, the topologies and morphologies of poly(ionic liquids) (PIL) govern their nano‐ and micro‐processibility. Modulating the interactions of cation‐anion pairs with aliphatic dipolar components enables the tunability of properties, facilitated by “bottom‐up ...
Jiahui Liu, Marek W. Urban
wiley   +1 more source

Neural Network Implementation in Java

BizInfo, 2020
Artificial neural networks are a powerful tool that engineers can use in variety of purposes. The most common tasks are classification and regression, as well as control, modeling and prediction.
Nenad Jovanović, Bojan Vasović, Zoran Jovanović, Miloš Cvjetković   +3 more
doaj   +1 more source

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

DECISION SYSTEM FOR STOCK DATA FORECASTING BASED ON HOPFIELD ARTIFICIAL NEURAL NETWORK

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2016
The paper describes a new method using Hopfield artificial neural network combined with technical analysis fractal analysis and feed-forward artificial neural networks for predicting share prices for a next day on a Stock Exchange.
Michał Paluch, Lidia Jackowska-Strumiłło   +1 more
doaj   +1 more source

On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks. [PDF]

PLoS ONE, 2013
A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems.
Paul Tonelli, Jean-Baptiste Mouret
doaj   +1 more source