Results 31 to 40 of about 5,079,190 (348)

Hybrid Gate-Level Leakage Model for Monte Carlo Analysis on Multiple GPUs

IEEE Access, 2014
This paper proposes a hybrid gate-level leakage model for the use with the Monte Carlo (MC) analysis approach, which combines a lookup table (LUT) model with a first-order exponential-polynomial model (first-order model, herein).
Jinwook Kim, Young Hwan Kim
doaj   +1 more source

AVATAR: NN-Assisted Variation Aware Timing Analysis and Reporting for Hardware Trojan Detection

IEEE Access, 2021
This paper presents AVATAR, a learning-assisted Trojan testing flow to detect hardware Trojans placed into fabricated ICs at an untrusted foundry, without needing a Golden IC.
Ashkan Vakil, Ali Mirzaeian, Houman Homayoun, Naghmeh Karimi, Avesta Sasan   +4 more
doaj   +1 more source

Regular variation of GARCH processes [PDF]

Stochastic Processes and their Applications, 2002
We show that the finite-dimensional distributions of a GARCH process are regularly varying, i.e., the tails of these distributions are Pareto-like and hence heavy-tailed. Regular variation of the joint distributions provides insight into the moment properties of the process as well as the dependence structure between neighboring observations when both ...
Basrak, Bojan, Davis, Richard A., Mikosch, Thomas Valentin   +2 more
openaire   +3 more sources

Yield improvement using configurable analogue transistors (CATs) [PDF]

, 2008
Continued process scaling has led to significant yield and reliability challenges for today’s designers. Analogue circuits are particularly susceptible to poor variation, driving the need for new yield resilient techniques in this area.
Bernstein, Hall, Kumar, Mcconaghy, P.R. Wilson, R. Wilcock   +5 more
core   +1 more source

An In-Memory-Computing Binary Neural Network Architecture With In-Memory Batch Normalization

IEEE Access
This paper describes an in-memory computing architecture that combines full-precision computation for the first and last layers of a neural network while employing binary weights and input activations for the intermediate layers.
Prathamesh Prashant Rege, Ming Yin, Sanjay Parihar, Joseph Versaggi, Shashank Nemawarkar   +4 more
doaj   +1 more source

An Energy-Efficient and High Throughput in-Memory Computing Bit-Cell With Excellent Robustness Under Process Variations for Binary Neural Network

IEEE Access, 2020
In-memory computing (IMC) is a promising approach for energy cost reduction due to data movement between memory and processor for running data-intensive deep learning applications on the computing systems.
Gobinda Saha, Zhewei Jiang, Sanjay Parihar, Cao Xi, Jack Higman, Muhammed Ahosan Ul Karim   +5 more
doaj   +1 more source

Accelerated Variational Dirichlet Process Mixtures [PDF]

, 2007
Dirichlet Process (DP) mixture models are promising candidates for clustering applications where the number of clusters is unknown a priori. Due to computational considerations these models are unfortunately unsuitable for large scale data-mining applications.
Kurihara, K., Welling, M., Vlassis, N.
openaire   +3 more sources

Design of the Squared Daisy: A Multi-Mode Energy Harvester, with Reduced Variability and a Non-Linear Frequency Response

Sensors, 2019
With the rise of the Internet of Things (IoT) and the ever-increasing number of integrated sensors, the question of powering these devices represents an additional challenge.
Mathieu Gratuze, Abdul Hafiz Alameh, Frederic Nabki   +2 more
doaj   +1 more source

Variational perturbation theory for Markov processes [PDF]

Physical Review E, 2002
Author Information under http://www.physik.fu-berlin.de/~kleinert/institution.html Latest update of paper also at http://www.physik.fu-berlin.de/~kleinert ...
Kleinert, Hagen, Pelster, Axel, Putz, Mihai V.   +2 more
openaire   +3 more sources

A Stochastic Decoder for Neural Machine Translation [PDF]

, 2018
The process of translation is ambiguous, in that there are typically many valid trans- lations for a given sentence. This gives rise to significant variation in parallel cor- pora, however, most current models of machine translation do not account for ...
Aziz, Wilker, Cohn, Trevor, Schulz, Philip   +2 more
core   +2 more sources