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Li, Siyue (author), Zhou, Shize (author), Xue, Yongqi (author), Fan, Wenjie (author), Cheng, Tong (author), Ji, Jinlun (author), Dai, Chenyang (author), Song, Wenqing (author), Gao, C. (author)Network-on-Chip (NoC) is a scalable on-chip communication architecture for the NN accelerator, but with the increase in the number of nodes, the communication delay becomes higher. Applications such as machine learning have a certain resilience to noisy/erroneous transmitted data. Therefore, approximate communication becomes a promising solution...journal article 2024
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Hadjisotiriou, George (author), Mansour Pour, K. (author), Voskov, D.V. (author)In this study, we utilize deep neural networks to approximate operators of a nonlinear partial differential equation (PDE), within the Operator-Based Linearization (OBL) simulation framework, and discover the physical space for a physics-based proxy model with reduced degrees of freedom. In our methodology, observations from a high-fidelity...conference paper 2023
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Aziza, Hassen (author), Zambelli, Cristian (author), Hamdioui, S. (author), Diware, S.S. (author), Bishnoi, R.K. (author), Gebregiorgis, A.B. (author)Emerging device technologies such as Resistive RAMs (RRAMs) are under investigation by many researchers and semiconductor companies; not only to realize e.g., embedded non-volatile memories, but also to enable energy-efficient computing making use of new data processing paradigms such as computation-in-memory. However, such devices suffer from...conference paper 2023
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Song, Q. (author), Tan, Rui (author), Wang, J. (author)Driver Behavior Modeling (DBM) aims to predict and model human driving behaviors, which is typically incorporated into the Advanced Driver Assistance System to enhance transportation safety and improve driving experience. Inverse reinforcement learning (IRL) is a prevailing DBM technique with the goal of modeling the driving policy by...conference paper 2023
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Kovacevic, Meho Sasa (author), Bačić, Mario (author), Librić, Lovorka (author), Gavin, Kenneth (author)To identify the unknown values of the parameters of Burger’s constitutive law, commonly used for the evaluation of the creep behavior of the soft soils, this paper demonstrates a procedure relying on the data obtained from multiple sensors, where each sensor is used to its best advantage. The geophysical, geotechnical, and unmanned aerial...journal article 2022
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de Bruijn, Douwe S. (author), ten Eikelder, Henricus R.A. (author), Papadimitriou, V. (author), Olthuis, Wouter (author), van den Berg, Albert (author)The assessment of particle and cell size in electrical microfluidic flow cytometers has become common practice. Nevertheless, in flow cytometers with coplanar electrodes accurate determination of particle size is difficult, owing to the inhomogeneous electric field. Pre-defined signal templates and compensation methods have been introduced to...journal article 2022
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Adibi, M. (author), van der Woude, J.W. (author)In this article, we present a reinforcement learning-based scheme for secondary frequency control of lossy inverter-based microgrids. Compared with the existing methods in the literature, we relax the common restrictions on the system, i.e., being lossless, and the transmission lines and loads to have known constant impedances. The proposed...journal article 2022
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van Kempen, J. (author), Santos, Bruno F. (author), Scherp, L. (author)This work addresses the cockpit crew training scheduling problem. The objective is to produce a robust cockpit crew training schedule, including the assignment of trainees, instructors and simulators. To attain this objective, we propose a scheduling framework composed of four modules: a Training Scheduling & Assignment Model (TS&AM),...journal article 2022
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Mohammadi, Majid (author)The fused lasso signal approximator (FLSA) is a vital optimization problem with extensive applications in signal processing and biomedical engineering. However, the optimization problem is difficult to solve since it is both nonsmooth and nonseparable. The existing numerical solutions implicate the use of several auxiliary variables in order...journal article 2021
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Akgün, O.C. (author), Mei, J. (author)This paper presents the design of an ultra-low energy neural network that uses time-mode signal processing). Handwritten digit classification using a single-layer artificial neural network (ANN) with a Softmin-based activation function is described as an implementation example. To realize time-mode operation, the presented design makes use of...journal article 2020
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Rushdi, Mostafa A. (author), Rushdi, Ahmad A. (author), Dief, Tarek N. (author), Halawa, Amr M. (author), Yoshida, Shigeo (author), Schmehl, R. (author)Kites can be used to harvest wind energy at higher altitudes while using only a fraction of the material required for conventional wind turbines. In this work, we present the kite system of Kyushu University and demonstrate how experimental data can be used to train machine learning regression models. The system is designed for 7 kW traction...journal article 2020
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Miedema, Rene (author), Smaragdos, Georgios (author), Negrello, Mario (author), Al-Ars, Z. (author), Möller, M. (author), Strydis, C. (author)The Hodgkin-Huxley (HH) neuron is one of the most biophysically-meaningful models used in computational neuroscience today. Ironically, the model's high experimental value is offset by its disproportional computational complexity. To such an extent that neuroscientists have either resorted to simpler models, losing precious neuron detail, or...journal article 2020
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Cao, Z. (author), Dong, J. (author), Wani, F.M. (author), Polinder, H. (author), Bauer, P. (author), Peng, Fei (author), Huang, Yunkai (author)A novel controller design procedure is proposed for a 5-degree-of-freedom (DOF) active magnetic bearing (AMB) system, based on sliding mode control (SMC) and neural network (NN). The SMC is used to achieve high robustness and fast response while the NN can compensate unmodeled uncertainty and external disturbance by on-line tuning algorithm. The...conference paper 2019
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Kim, Jaehun (author), Urbano, Julián (author), Liem, C.C.S. (author), Hanjalic, A. (author)Deep neural networks have frequently been used to directly learn representations useful for a given task from raw input data. In terms of overall performance metrics, machine learning solutions employing deep representations frequently have been reported to greatly outperform those using hand-crafted feature representations. At the same time,...journal article 2019
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Kim, Jaehun (author), Won, Minz (author), Serra, Xavier (author), Liem, C.C.S. (author)The automated recognition of music genres from audio information is a challenging problem, as genre labels are subjective and noisy. Artist labels are less subjective and less noisy, while certain artists may relate more strongly to certain genres. At the same time, at prediction time, it is not guaranteed that artist labels are available for a...conference paper 2018
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Khuntia, S.R. (author), Rueda, José L. (author), van der Meijden, M.A.M.M. (author)Load forecasting is considered vital along with many other important entities required for assessing the reliability of power system. Thus, the primary concern is not to forecast load with a novel model, rather to forecast load with the highest accuracy. Short-term load forecast accuracy is often hindered due to various load impacting factors....conference paper 2016
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- Liu, H. (author), Redi, J. (author), Alers, H. (author), Zunino, R. (author), Heyndrinckx, I. (author) conference paper 2010
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Miradi, M. (author)The main goal of the study was to discover knowledge from data about asphalt road pavement problems to achieve a better understanding of the behavior of them and via this understanding improve pavement quality and enhance its lifespan. Four pavement problems were chosen to be investigated; raveling of Porous Asphalt Concrete (PAC), cracking of...doctoral thesis 2009
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Van Oosten, R.P. (author), Peixó Marco, J. (author), Van der Meer, J.W. (author), Van Gent, M. (author), Verhagen, H.J. (author)The European Union funded project DELOS was focused on wave transmission and an extensive database on low-crested rubble mound structures was generated. During DELOS, new empirical wave transmission formulae were derived. These formulae still showed a considerable scatter due to a limited number of parameters included. Neural networks based on a...conference paper 2006
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- Van der Wolk, P.J. (author) doctoral thesis 2001
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