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A unified framework for nonlinear dependence testing and symbolic analysis

Robert A. van Engelen, J. Birch, Y. Shou, B. Walsh, Kyle A. Gallivan
2004 Proceedings of the 18th annual international conference on Supercomputing - ICS '04  
region analysis, and nonlinear dependence testing.  ...  This uniform approach provides a powerful unified framework of analysis methods for restructuring compilers.  ...  This approach provides a powerful new unified framework for nonlinear symbolic analysis in restructuring compilers.  ... 
doi:10.1145/1006209.1006226 dblp:conf/ics/EngelenBSWG04 fatcat:hkwj7as4dvcydfx76hqxp7cybi


Andres Marcos, Declan G. Bates, Ian Postlethwaite
2005 IFAC Proceedings Volumes  
In this paper, a nonlinear modelling framework is presented that combines symbolic modelling and linear fractional transformation (LFT) techniques to obtain a nonlinear symbolic LFT representation.  ...  This modelling approach presents three clear advantages: (i) it provides a unifying framework for the different models that stem from the same nonlinear system, (ii) it allows for a highly structured representation  ...  Firstly, it provides a unifying framework for the different models that stem from the same nonlinear system, and thus improves consistency, continuity and connectedness between these various models.  ... 
doi:10.3182/20050703-6-cz-1902.00032 fatcat:p3yl2brtjzghdmt4g6gvdmroiy

Unified Embedded Parallel Finite Element Computations via Software-Based Fréchet Differentiation

Kevin Long, Robert Kirby, Bart van Bloemen Waanders
2010 SIAM Journal on Scientific Computing  
Moving beyond the automation of discretization of PDEs by finite element methods, we present a mathematical framework that unifies the discretization of PDEs with these additional analysis requirements  ...  Sundance is a C++ library for symbolically representing, manipulating, and evaluating variational forms, together with necessary lower-level finite element tools.  ...  The component in shaded box is framework-dependent; others are framework-independent.  ... 
doi:10.1137/09076920x fatcat:mbebasijuvg7tg4b3v2uwtdfia

Temperature and frequency dependent mean free paths of renormalized phonons in nonlinear lattices

Nianbei Li, Junjie Liu, Changqin Wu, Baowen Li
2018 New Journal of Physics  
The typical 1D nonlinear lattices such as Fermi-Pasta-Ulam β lattice and f 4 lattice are investigated in detail.  ...  In this work, we directly study the temperature and frequency dependent mean free path (MFP) of renormalized phonons with the newly developed numerical tuning fork method.  ...  Since the heat conduction is normal for the f 4 lattice, we are able to test both the frequency and temperature dependence of MFPs here.  ... 
doi:10.1088/1367-2630/aaa4a8 fatcat:avis3ktakjfgxeuzfi6il57rnm

A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron

S. Ortín, M. C. Soriano, L. Pesquera, D. Brunner, D. San-Martín, I. Fischer, C. R. Mirasso, J. M. Gutiérrez
2015 Scientific Reports  
The ESNs were inspired in recurrent neural networks, suitable for time dependent data. In this paper we propose a unified framework for random-projection machines, based on ESNs and ELMs.  ...  In this paper we present a unified framework for extreme learning machines and reservoir computing (echo state networks), which can be physically implemented using a single nonlinear neuron subject to  ...  This work has been funded by the Ministerio de Econom a y Competitividad, Spain, under project TEC2012-38864-C03-03 and co-financed by FEDER funds.  ... 
doi:10.1038/srep14945 pmid:26446303 pmcid:PMC4597340 fatcat:k6d3mgbwwjewbe3ikd6mr3bduy

Memory-access-aware Safety and Profitability Analysis for Transformation of Accelerator-bound OpenMP Loops

Artem Chikin, Taylor Lloyd, José Nelson Amaral, Ettore Tiotto, Muhammad Usman
2019 ACM Transactions on Architecture and Code Optimization (TACO)  
This analysis framework enables safe and profitable loop transformations. Experimental results demonstrate potential for dramatic performance improvements.  ...  Iteration Point Difference Analysis is a new static analysis framework that can be used to determine the memory coalescing characteristics of parallel loops that target GPU offloading and to ascertain  ...  Engelen et al. propose a symbolic loop analysis framework for nonlinear dependence testing based on a representation of symbolic expressions with chains of recurrences (CRs) [31] .  ... 
doi:10.1145/3333060 fatcat:jvbz2btb55e4hk3mtvs4scfrje

Symbolic-Numeric Methods for Problem Solving in CPS (Dagstuhl Seminar 16491)

Sergiy Bogomolov, Martin Fränzle, Kyoko Makino, Nacim Ramdani, Marc Herbstritt
2017 Dagstuhl Reports  
means of error-propagation analysis; numerical and/or symbolic methods such as verified integrations, interval methods and arithmetic constraint solving; reactive and in-advance planning and optimization  ...  Reflecting the fundamental role numeric and mixed symbolic-numeric arguments play in the analysis, decision making, and control of cyber-physical processes, this seminar promoted crossfertilization between  ...  Hence attribute grammars may serve as a unifying framework to describe workflow and planning domains models.  ... 
doi:10.4230/dagrep.6.12.1 dblp:journals/dagstuhl-reports/BogomolovFMR16 fatcat:sydj4slvefa7boehai7gpnfupm

A Survey on Binary Code Vulnerability Mining Technology

Pengzhi Xu, Zetian Mai, Yuhao Lin, Zhen Guo, Victor S. Sheng
2021 Journal of Information Hiding and Privacy Protection  
Based on the investigation of related technologies, this article firstly introduces the current typical binary vulnerability analysis framework, and then briefly introduces the research background and  ...  significance of the intermediate language; with the rise of artificial intelligence, a large number of machine learning methods have been tried to solve the problem of binary vulnerability mining.  ...  Acknowledgement: The authors would like to thank the partners for their hard work, as well as the reviewers for their detailed review and valuable comments.  ... 
doi:10.32604/jihpp.2021.027280 fatcat:3l22xfqflnafdpydya45std7ey

Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds

Elnaz Barshan, Ali Ghodsi, Zohreh Azimifar, Mansoor Zolghadri Jahromi
2011 Pattern Recognition  
We propose "Supervised Principal Component Analysis (Supervised PCA)", a generalization of PCA that is uniquely effective for regression and classification problems with high-dimensional input data.  ...  It works by estimating a sequence of principal components that have maximal dependence on the response variable.  ...  This algorithm provides a nonlinear projection of the given training data, but has no straightforward extension for the new test points.  ... 
doi:10.1016/j.patcog.2010.12.015 fatcat:baocam3kwjh3blfd7gvziyondq

Low Frequency Oscillation Mode Estimation Using Synchrophasor Data

Jinhuan Zhang, Haixia An, Na Wu
2020 IEEE Access  
Deep learning techniques have been widely used for power system operations as a very hot topic in recent years.  ...  ., IEEE 39-bus system and IEEE 118-bus system, by comparing with the Nonlinear Autoregressive Neural Network with External Input (NARX), the Gated Recurrent Unit (GRU) network, and single LSTM methods.  ...  The Hilbert-Huang transform (HHT), as a time-frequency analysis method for nonlinear signals, is focused on the time-varying characteristics of nonlinear signals.  ... 
doi:10.1109/access.2020.2982979 fatcat:qk67uqkl2rbx5cywetwujutsd4


D. Rubin, G. Aldering, K. Barbary, K. Boone, G. Chappell, M. Currie, S. Deustua, P. Fagrelius, A. Fruchter, B. Hayden, C. Lidman, J. Nordin (+3 others)
2015 Astrophysical Journal  
We present a new Bayesian framework, called UNITY (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to confront these effects.  ...  We verify earlier results that SNe Ia require nonlinear shape and color standardizations, but we now include these nonlinear relations in a statistically well-justified way.  ...  We thank Alex Kim, Marisa March, Masao Sako, Rachel Wolf, and  ... 
doi:10.1088/0004-637x/813/2/137 fatcat:f6i53sm5i5bzjdb6xcm33ddyia

A unified theory of chaos linking nonlinear dynamics and statistical physics [article]

Chi-Sang Poon, Cheng Li, Guo-Qiang Wu
2010 arXiv   pre-print
These findings lay the foundation for reliable analysis of low-dimensional chaos for complex systems modeling and prediction of a wide variety of physical, biological, and socioeconomic data.  ...  A fundamental issue in nonlinear dynamics and statistical physics is how to distinguish chaotic from stochastic fluctuations in short experimental recordings.  ...  These observations lead to a powerful test of lowdimensional chaos under measurement and dynamic noise that is applicable to the modeling A unified theory of chaos linking nonlinear dynamics and statistical  ... 
arXiv:1004.1427v1 fatcat:w3rw7bp5wzbhbb2vggbvhai4fa

An Approach to a Nonlinear Electrodynamics in Curved Space-Time

A. J. Accioly, N. L. P. P. d. Silva
1986 Progress of theoretical physics  
A nonlinear electrodynamics is generated via gravitational nonminimal coupling.  ...  a positive one is also exhibited.  ...  The symbol "/" stands in principle for anyone of the electromagnetic invariants regarding the curved space-time. As usual, A is a coupling constant.  ... 
doi:10.1143/ptp.76.1179 fatcat:37cmylczt5ba5cawsexkkm74py

Verification of Cyber-Physical Systems (Dagstuhl Seminar 14122)

Rupak Majumdar, Richard M. Murray, Pavithra Prabhakar, Marc Herbstritt
2014 Dagstuhl Reports  
This is a multi-disciplinary area requiring collaboration between areas focusing discrete systems analysis and continuous systems analysis.  ...  Cyber-physical systems refer to a new genre of engineered systems consisting of a tight coupling between computation, communication and physical entities.  ...  can lead to scalable stability analysis tests for linear and switched linear systems (with state dependent switching).  ... 
doi:10.4230/dagrep.4.3.85 dblp:journals/dagstuhl-reports/MajumdarMP14 fatcat:qm5epthwvbgf5mk74me42qcpei

On improving the numerical convergence of highly nonlinear elasticity problems

Yue Mei, Daniel E. Hurtado, Sanjay Pant, Ankush Aggarwal
2018 Computer Methods in Applied Mechanics and Engineering  
The proposed framework is generic and can be applied to other types of nonlinearities as well.  ...  We study exponential-type nonlinearity in soft tissues and geometric nonlinearity in compression, and propose novel formulations for the two problems.  ...  line and filled symbols) for (a) varying B and (b) varying K/A.  ... 
doi:10.1016/j.cma.2018.03.033 fatcat:hcryzwoiljeihpiliq6vchyce4
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