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Anomaly detection or more generally outliers detection is one of the most popular and challenging subject in theoretical and applied machine learning. The main challenge is that in general we have access to very few labeled data or no…

Machine Learning · Computer Science 2023-05-31 Mansour Zoubeirou A Mayaki , Michel Riveill

Diffractive neural networks (DNNs) are an emerging approach for the realization of photonic artificial intelligence, especially due to their suitability for machine-vision applications and high-dimensional photonic information processing at…

Optics · Physics 2026-03-27 Marie Braasch , Anna Kartashova , Elena Goi , Thomas Pertsch , Sina Saravi

This study presents a sampling-based method to guarantee robust stability of general control systems with uncertainty. The method allows the system dynamics and controllers to be represented by various data-driven models, such as Gaussian…

Optimization and Control · Mathematics 2025-04-11 Yuji Ito , Kenji Fujimoto

This contribution Part II of a two-part series, extends the general-domain FC-SDNN (Fourier Continuation Shock-Detecting Neural Network) introduces in Part I to enable treatment of non-smooth domains, it introduces a parallel implementation…

Numerical Analysis · Mathematics 2025-06-25 Daniel V. Leibovici , Oscar P. Bruno

The equivalence between integral-chain differentiator and usual high-gain differentiator is given under suitable coordinate transformation. Integral-chain differentiator can restrain noises more thoroughly than usual high-gain linear…

Systems and Control · Computer Science 2011-02-15 Xinhua Wang

Lane detection is an integral part of control systems in autonomous vehicles and lane departure warning systems as lanes are a key component of the operating environment for road vehicles. In a previous paper, a robust neural network output…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Zhe Ming Chng , Joseph Mun Hung Lew , Jimmy Addison Lee

Active learning aims to improve the performance of task model by selecting the most informative samples with a limited budget. Unlike most recent works that focused on applying active learning for image classification, we propose an…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Weiping Yu , Sijie Zhu , Taojiannan Yang , Chen Chen

Self-triggered control (STC) is a well-established technique to reduce the amount of samples for sampled-data systems, and is hence particularly useful for Networked Control Systems. At each sampling instant, an STC mechanism determines not…

Systems and Control · Electrical Eng. & Systems 2021-09-15 Michael Hertneck , Frank Allgöwer

This work presents the Second-Order Sensitivity Analysis Methodology (2nd-ASAM) for nonlinear systems. This methodology yields exactly and efficiently the second-order functional derivatives of system responses (associated with physical,…

Optimization and Control · Mathematics 2016-01-26 Dan Gabriel Cacuci

In this paper the stability of a closed-loop cascade control system in the trajectory tracking task is addressed. The considered plant consists of underlying second-order fully actuated perturbed dynamics and the first order system which…

Systems and Control · Electrical Eng. & Systems 2020-02-05 Radosław Patelski , Dariusz Pazderski

Ordinal regression is commonly formulated as a multi-class problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal regression generally increases with the number of classes involved, due to the large…

Machine Learning · Computer Science 2015-03-18 Chun-Wei Seah , Ivor W. Tsang , Yew-Soon Ong

For computational acoustics, schemes need to have low-dispersion and low-dissipation properties in order to capture the amplitude and phase of the wave correctly. To improve the spectral properties of the scheme, the authors have previously…

Computational Physics · Physics 2021-11-15 Y. H. Li , Y. X. Ren , Y. T. Su

In harmonic radar (HR), the radio frequency transmitter illuminates a nonlinear target (the tag), causing the return signal to consist of harmonics at multiples of the transmitted carrier frequency. Of them, the second harmonic is usually…

Signal Processing · Electrical Eng. & Systems 2022-05-11 Anastasia Lavrenko , James K. Cavers , Graeme K. Woodward

Adversarial training is a common approach to improving the robustness of deep neural networks against adversarial examples. In this work, we propose a novel regularization approach as an alternative. To derive the regularizer, we formulate…

Machine Learning · Computer Science 2021-02-09 Avery Ma , Fartash Faghri , Nicolas Papernot , Amir-massoud Farahmand

This paper proposes an approach to addresses the control challenges posed by a fault-induced uncertainty in both the dynamics and control input effectiveness of a class of hierarchical nonlinear systems in which the high-level dynamics is…

Optimization and Control · Mathematics 2021-08-10 Sina Ameli , Olugbenga Moses Anubi

We introduce a data-driven anomaly detection framework using a manufacturing dataset collected from a factory assembly line. Given heterogeneous time series data consisting of operation cycle signals and sensor signals, we aim at…

Artificial Intelligence · Computer Science 2022-02-11 Kyeong-Joong Jeong , Jin-Duk Park , Kyusoon Hwang , Seong-Lyun Kim , Won-Yong Shin

This paper proposes a new nonlinear stability analysis for the acceleration-based robust position control of robot manipulators by using Disturbance Observer (DOb). It is shown that if the nominal inertia matrix is properly tuned in the…

Systems and Control · Computer Science 2019-02-22 Emre Sariyildiz , Hiromu Sekiguchi , Takahiro Nozaki , Barkan Ugurlu , Kouhei Ohnishi

This paper proposes an original solution to input saturation and dead zone of fractional order system. To overcome these nonsmooth nonlinearities, the control input is decomposed into two independent parts by introducing an intermediate…

Optimization and Control · Mathematics 2024-12-20 Dian Sheng , Yiheng Wei , Songsong Cheng , Yong Wang

In this paper, a novel finite - time Nonlinear Extended State Observer (NLESO) is proposed and employed in Active Disturbance Rejection Control (ADRC) to stabilize a nonlinear system against system's uncertainties and discontinuous…

Systems and Control · Computer Science 2019-04-02 Ibraheem Kasim Ibraheem , Amjad J. Humaidi

It is well-known that third-order dispersion (TOD) never allows the continuous wave of any nonlinear Schroedinger (NLS) type system to experience modulational instability (MI). Remarkably, we demonstrate a new kind of MI induced by TOD with…

Pattern Formation and Solitons · Physics 2020-12-01 K. Tamilselvan , A. Govindarajan , T. Kanna , M. Lakshmanan , P. Tchofo-Dinda