Results 101 to 110 of about 37,233 (256)
Robust and Compatible Ferroelectric Memories with Polycrystalline TiO2 Channel for 3D Integration
Robust and monolithic 3D compatible ferroelectric memories are realized using the polycrystalline TiO2 channel‐based FeFET. The review covers physical mechanisms of the TiO2 channel FeFET, quantitative benchmarking, and advanced planar/vertical architectures for monolithic 3D integration based on HfO2‐TiO2 gate stack, offering a roadmap for reliable ...
Xujin Song +10 more
wiley +1 more source
A Cognitive Load Theory-Informed Attention Mechanism for Transformer-Based Text Classification
We propose a Cognitive Load Theory (CLT)-informed attention mechanism for transformer-based text classification. The proposed attention mechanism computes a per-token cognitive-load signal—derived from attention entropy, margin-based classification ...
Jarrod Graham, Victor S. Sheng
doaj +1 more source
DecoHD: Decomposed Hyperdimensional Classification under Extreme Memory Budgets
Decomposition is a proven way to shrink deep networks without changing input-output dimensionality or interface semantics. We bring this idea to hyperdimensional computing (HDC), where footprint cuts usually shrink the feature axis and erode concentration and robustness.
Sanggeon Yun +3 more
openaire +2 more sources
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
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
A novel strategy is used to fabricate multi‐threshold‐voltage (multi‐Vth) IGZO FETs via continuous‐wave laser scanning annealing (CW‐LSA). By tuning the laser power and scan speed, low, standard, and high Vth values of 0.22, 0.42, and 0.62 V, respectively, were achieved on a single wafer with excellent uniformity (coefficient of variation: 2.17%–6.61%).
Jun‐Hyeok Choi +8 more
wiley +1 more source
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
Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka +5 more
wiley +1 more source
Simultaneous Latent Budget Trees for Stratified Classification
In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper introduces Simultaneous Latent Budget Trees, a probabilistic machine learning framework for classification trees in the presence of a stratification factor such as a temporal, spatial, or demographic variable, acting ...
Buoncompagni, Simultaneous Latent Budget Trees for Stratified Classification Cristian +4 more
openaire +2 more sources
Environmental Effects on RRAM Cells Based on 2D Halide Perovskite Materials
RRAM offers high speed, scalability, and low power, positioning it as a next‐generation non‐volatile memory. Two‐dimensional halide perovskites show promise due to tunable optoelectronic properties and flexible processing but suffer from environmental sensitivity. This review examines degradation from humidity, temperature, light, and strain, discusses
Mojtaba Joodaki +3 more
wiley +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source

