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Drug discovery is a highly complicated process, and it is unfeasible to fully commit it to the recently developed molecular generation methods. Deep learning-based lead optimization takes expert knowledge as a starting point, learning from…

Partial Information Decomposition (PID) is a principled and flexible method to unveil complex high-order interactions in multi-unit network systems. Though being defined exclusively for random variables, PID is ubiquitously applied to…

A finite element method for solving nonlinear differential equations on a grid, with potential applicability to computational fluid dynamics (CFD), is developed and tested. The current method facilitates the computation of solutions of a…

Computational Physics · Physics 2014-09-04 Jesper Tveit

In this paper, a novel adaptive tuning method of PID neural network (PIDNN) controller for nonlinear process is proposed. The method utilizes an improved gradient descent method to adjust PIDNN parameters where the margin stability will be…

Systems and Control · Computer Science 2015-12-24 Ali Zribi , Mohamed Chtourou , Mohamed Djemel

Detection of level shifts in a noisy signal, or trend break detection, is a problem that appears in several research fields, from biophysics to optics and economics. Although many algorithms have been developed to deal with such problem,…

Signal Processing · Electrical Eng. & Systems 2019-02-19 Felipe Calliari , Gustavo C. Amaral , Michael Lunglmayr

In this paper, taking the view that a linear parallel interference canceller (LPIC) can be seen as a linear matrix filter, we propose new linear matrix filters that can result in improved bit error performance compared to other LPICs in the…

Information Theory · Computer Science 2007-09-17 T. Srikanth , K. Vishnu Vardhan , A. Chockalingam , L. B. Milstein

We develop a novel multi-layer predictor-feedback to achieve exact compensation of state-dependent input delay of general nonlinear integro-differential equations. The system of interest is an unconventional mixed Partial Differential…

Optimization and Control · Mathematics 2026-04-09 Tong Li , Peipei Shang , Mamadou Diagne

By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-feedback and state-feedback-based LPV-DPC methods with terminal…

Systems and Control · Electrical Eng. & Systems 2026-02-26 Chris Verhoek , Julian Berberich , Sofie Haesaert , Roland Tóth , Hossam S. Abbas

A high-dimensional and incomplete (HDI) matrix frequently appears in various big-data-related applications, which demonstrates the inherently non-negative interactions among numerous nodes. A non-negative latent factor (NLF) model performs…

Machine Learning · Computer Science 2022-10-25 Ye Yuan , Xin Luo

We present the two kinds of experimental results. One is a continuous variable dense coding experiment, and the other is a photon number detector with high linearity response, the so called charge integration photon detector (CIPD). They…

Quantum Physics · Physics 2007-05-23 M. Sasaki , K. Wakui , J. Mizuno , M. Fujiwara , M. Akiba

Cracking Elements Method (CEM) is a numerical tool to simulate quasi-brittle fractures, which does not need remeshing, nodal enrichment, or complicated crack tracking strategy. The cracking elements used in the CEM can be considered as a…

Computational Engineering, Finance, and Science · Computer Science 2024-07-25 Xueya Wang , Yiming Zhang , Minjie Wen , Herbert Mang

Semi-Inclusive Deep Inelastic Scattering (SIDIS) is a key tool for exploring the three-dimensional structure of the nucleon through Transverse Momentum Dependent parton distributions and fragmentation functions. While leading-power…

High Energy Physics - Phenomenology · Physics 2026-01-28 Ian Balitsky , Alexei Prokudin

A simple procedure for the design of recursive digital filters with an infinite impulse response (IIR) and non-recursive digital filters with a finite impulse response (FIR) is described. The fixed-lag smoothing filters are designed to…

Signal Processing · Electrical Eng. & Systems 2025-07-22 Hugh Lachlan Kennedy

Water quality data can supply a substantial decision support for water resources utilization and pollution prevention. However, there are numerous missing values in water quality data due to inescapable factors like sensor failure, thereby…

Machine Learning · Computer Science 2025-03-11 Qian Liu , Lan Wang , Bing Yang , Hao Wu

Due to the wide separation of time scales in geophysical fluid dynamics, semi-implicit time integrators are commonly used in operational atmospheric forecast models. They guarantee the stable treatment of fast (acoustic and gravity) waves,…

Computational Physics · Physics 2020-12-30 Christopher Maynard , Thomas Melvin , Eike Hermann Müller

Probabilistic Manifold Decomposition (PMD)\cite{doi:10.1137/25M1738863}, developed in our earlier work, provides a nonlinear model reduction by embedding high-dimensional dynamics onto low-dimensional probabilistic manifolds. The PMD has…

Numerical Analysis · Mathematics 2026-01-13 Jiaming Guo , Dunhui Xiao

In this paper, we introduce the proper latent decomposition (PLD) as a generalization of the proper orthogonal decomposition (POD) on manifolds. PLD is a nonlinear reduced-order modeling technique for compressing high-dimensional data into…

Machine Learning · Computer Science 2024-12-03 Daniel Kelshaw , Luca Magri

In the design flow of integrated circuits, chip-level verification is an important step that sanity checks the performance is as expected. Power grid verification is one of the most expensive and time-consuming steps of chip-level…

Other Computer Science · Computer Science 2015-07-09 Jim Jing-Yan Wang , Lan Yang , Jingbin Wang , Lorenzo Azevedo

This paper suggests to replace PIs and PIDs, which play a key role in control engineering, by intelligent Proportional-Derivative feedback loops, or iPDs, which are derived from model-free control. This standpoint is enhanced by a…

Systems and Control · Electrical Eng. & Systems 2021-07-08 Michel Fliess , Cédric Join

The dissipativity framework is widely used to analyze stability and performance of nonlinear systems. By embedding nonlinear systems in an LPV representation, the convex tools of the LPV framework can be applied to nonlinear systems for…

Systems and Control · Electrical Eng. & Systems 2021-09-21 Patrick J. W. Koelewijn , Roland Tóth
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