Results 121 to 130 of about 3,022,789 (295)

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

open access: yesAdvanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan   +4 more
wiley   +1 more source

Random Vectors in the Isotropic Position

open access: yesJournal of Functional Analysis, 1999
Let $y$ be a random vector in \rn, satisfying $$ \Bbb E \, \tens{y} = id. $$ Let $M$ be a natural number and let $y_1 \etc y_M$ be independent copies of $y$. We prove that for some absolute constant $C$ $$ \enor{\frac{1}{M} \sum_i \tens{y_i} - id} \le C \cdot \frac{\sqrt{\log M}}{\sqrt{M}} \cdot \left ( \enor{y}^{\log M} \right )^{1/ \log M ...
openaire   +3 more sources

Load Distributing Metamaterials Via Discrete Optimization

open access: yesAdvanced Functional Materials, EarlyView.
Mechanical metamaterials are computationally optimized to homogenize transmitted forces by minimizing the spread of reaction forces. The resulting architectures transform localized loading into broader, more uniform force distributions and experimentally demonstrate robust load spreading under quasi‐static and impact loading.
Andrea Detry   +6 more
wiley   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

open access: yesAdvanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar   +9 more
wiley   +1 more source

Respiratory Motion Prediction with Empirical Mode Decomposition-Based Random Vector Functional Link

open access: yesMathematics
The precise prediction of tumor motion for radiotherapy has proven challenging due to the non-stationary nature of respiration-induced motion, frequently accompanied by unpredictable irregularities. Despite the availability of numerous prediction methods
Asad Rasheed, Kalyana C. Veluvolu
doaj   +1 more source

Thermoresponsive Liquid Crystalline Polymer Coatings Programmed by Field‐Induced Topological Defects for Tunable Optical and Topographical Responses

open access: yesAdvanced Functional Materials, EarlyView.
Resonant standing waves generate large‐area lattices of liquid‐crystal topological defects that are permanently encoded into polymer coatings by photopolymerization. The preserved director architecture produces thermally reconfigurable surface topographies while maintaining programmable optical functionality, demonstrating a scalable strategy for ...
Jacques A. Peixoto   +6 more
wiley   +1 more source

Enhanced Ferroelectric Phase Formation via Local Structure Modification in the Pre‐Crystalline State of Hafnium Zirconium Oxide Thin Films

open access: yesAdvanced Functional Materials, EarlyView.
Hafnium zirconium oxide thin films are grown using plasma‐enhanced atomic layer deposition with the addition of an atomic layer annealing (ALA) step. ALA leads to a change in the short‐range structure of the deposit and encourages formation of the ferroelectric Pca21 phase. The result is wake‐up‐free performance with films exposed to ALA.
Nicolas K. Lam   +18 more
wiley   +1 more source

Random Sums of Random Variables and Vectors [PDF]

open access: yes, 2009
Let fX;Xi; i = 1; 2; :::g denote independent positive random variables having a common distribution function F(x) and, independent of X, let N denote an integer valued random variable. Using S(0) = 0 and S(n) = S(n ?? 1) + Xn, the random sum S(N) has distribution function G(x) = 1Xi=0 P(N = i)P(S(i) _ x) and tail distribution G(x) = 1 ?? G(x). In which
Omey, Edward, Vesilo, R.
openaire   +2 more sources

K-differenced vector random fields

open access: yes, 2015
Thesis (Ph.D.)-- Wichita State University, Fairmount College of Liberal Arts and Sciences, Dept. of Mathematics, Statistics, and PhysicsThere is a great demand for analyzing multivariate measurements observed across space and over time, due to an ...
Alsultan, Rehab
core  

A Hybrid Random Forest based Support Vector Machine Classification Supplemented by Boosting [PDF]

open access: yes, 2014
This paper presents an approach to classify remote sensed data using a hybrid classifier. Random forest, Support Vector machines and boosting methods are used to build the said hybrid classifier.
Tarun Rao
core  

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