Results 91 to 100 of about 72,703 (318)
Forecasting linear dynamical systems using subspace methods [PDF]
A new procedure to predict with subspace methods is presented in this paper. It is based on combining multiple forecasts obtained from setting a range of values for a specic parameter that is typically xed by the user in the subspace methods literature ...
Alfredo García-Hiernaux
core
Subspace-hypercyclic weighted shifts
, 2018 Our aim in this paper is to obtain necessary and sufficient conditions for bilateral and unilateral weighted shift operators to be subspace-transitive. We show that the Herrero question [6] holds true even on a subspace of a Hilbert space, i.e.
Nareen Bamerni +3 more
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Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
IEEE AccessAs wireless communication technology rapidly develops, multipath channel effects pose a severe challenge to the effectiveness of orthogonal frequency division multiplexing systems.
Jinyu Guo
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Quality-Driven Kernel Projection to Latent Structure Model for Nonlinear Process Monitoring
IEEE Access, 2019 A novel quality-driven kernel projection to latent structure (QKPLS) modeling scheme is proposed for concurrent quality-related and process-fault detection for nonlinear processes.
Qingchao Jiang, Xuefeng Yan
doaj +1 more source
The Performance of Subspace Algorithm Cointegration Analysis: A Simulation Study [PDF]
This paper presents a simulation study that assesses the finite sample performance of the subspace algorithm cointegration analysis developed in Bauer und Wagner (2002b).
Martin Wagner, Dietmar Bauer
core
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Proceedings of the forty-fourth annual ACM symposium on Theory of computing, 2012 In this work we describe an explicit, simple, construction of large subsets of F^n, where F is a finite field, that have small intersection with every k-dimensional affine subspace. Interest in the explicit construction of such sets, termed subspace-evasive sets, started in the work of Pudlak and Rodl (2004) who showed how such constructions over the ...
Zeev Dvir, Shachar Lovett
openaire +3 more sources
Unit Roots and Cointegrating Matrix Estimation using Subspace Methods [PDF]
We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series.
José Casals +2 more
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