Results 131 to 140 of about 110,493 (310)

Solution‐Processed Thin‐Film Transistors With Tunable Temporal Dynamics for Neuromorphic Computing

open access: yesAdvanced Functional Materials, EarlyView.
Solution‐processed CNT and CNT/P3HT ion‐gated transistors exhibit materials‐defined synaptic timescales: fast CNT devices for high‐frequency spiking and slow hybrid devices for temporal integration. Embedding these dynamics into coupled reservoir‐computing and spiking neural network simulations reveals that a Hybrid‐Reservoir / CNT‐SNN architecture ...
Kevin Schnittker   +5 more
wiley   +1 more source

Long-term gene therapy causes transgene-specific changes in the morphology of regenerating retinal ganglion cells

open access: yes, 2012
Recombinant adeno-associated viral (rAAV) vectors can be used to introduce neurotrophic genes into injured CNS neurons, promoting survival and axonal regeneration.
Rodger Jennifer   +14 more
core   +1 more source

Ultrasmall High‐Entropy Materials: Nanoscale Effects, Synthesis, and Mechanistic Insights

open access: yesAdvanced Functional Materials, EarlyView.
This review article focuses on sub‐10 nm high‐entropy materials that combine nanoscale design with complex compositions for next‐generation applications. ABSTRACT Ultrasmall high‐entropy nanomaterials (USHENMs, <10 nm) merge multicomponent chemistry with size‐dependent effects, forming a distinct class of materials with unprecedented properties.
Yueyue He   +5 more
wiley   +1 more source

Efficient K-Means VLSI Architecture for Vector Quantization

open access: yes, 2011
[[abstract]]A novel hardware architecture for k-means clustering is presented in this paper. Our architecture is fully pipelined for both the partitioning and centroid computation operations so that multiple training vectors can be concurrently processed.
Hsu, Chih-Chieh   +3 more
core  

Reconfigurable Logic Embedded Architecture of Support Vector Machine Linear Kernel

open access: yes, 2017
Support Vector  Machine  (SVM) is a linear  binary classifier  that  requires a  kernel  function  to  handle  non-linear problems.  Most  previous  SVM  implementations for  embedded systems  in literature were  built  targeting a certain  application ...
Shaikh-Husin, N.; Universiti Teknologi Malaysia   +3 more
core   +1 more source

Vorticity‐Driven µ‐Platelet Rotation and Selective Packing for Vertical Thermal–Electrical Interconnects

open access: yesAdvanced Functional Materials, EarlyView.
We introduce a capillary‐filtering‐based particle‐filling (CFPF) process that simultaneously forms vertical thermal pathways and electrical vias within µ‐pores. In situ microfluidic analysis reveals that capillary‐driven velocity gradients generate vorticity that governs µ‐platelet rotation and vertical alignment.
Yujin Mun   +11 more
wiley   +1 more source

Oxidized MoS2‐Based Multifunctional Memristive Hardware for Energy‐Efficient mmWave Signal Processing and In‐Memory Matrix Multiplication

open access: yesAdvanced Functional Materials, EarlyView.
Thermally oxidized MoS2‐based radio‐frequency switches enable a multifunctional platform that unifies broadband RF switching and in‐memory computation. The device achieves a cutoff frequency of 33.2 THz with high energy efficiency and supports hardware‐aware signal processing.
Juho Son   +5 more
wiley   +1 more source

An Application of Personalized PageRank Vectors: Personalized Search Engine

open access: yes, 2008
. We introduce a tool which is an application of personalized pagerank vectors such as personalized search engines. We use pre-computed pagerank vectors to rank the search results in favor of user preferences.
Mehmet S. Aktas, Mehmet A. Nacar
core  

System Architecture Optimization: Function-Based Modeling, Optimization Algorithms, and Multidisciplinary Evaluation [PDF]

open access: yes
When designing complex systems, choices related to the system architecture, the description of the functions and components of a system, greatly influence to which extent design goals can be achieved.
Bussemaker, Jasper, H.   +2 more
core   +1 more source

Empowering Vector Architectures for ML: The CAMP Architecture for Matrix Multiplication

open access: yesProceedings of the 58th IEEE/ACM International Symposium on Microarchitecture
This study presents the Cartesian Accumulative Matrix Pipeline (CAMP) architecture, a novel approach designed to enhance matrix multiplication in Vector Architectures (VAs) and Single Instruction Multiple Data (SIMD) units. CAMP improves the processing efficiency of Quantized Neural Networks (QNNs).
Mohammadreza Esmali Nojehdeh   +9 more
openaire   +2 more sources

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