Results 21 to 30 of about 39,760 (245)
One-Shot Bipedal Robot Dynamics Identification With a Reservoir-Based RNN
IEEE Access, 2023 The nonlinear inverted pendulum model of a lightweight bipedal robot is identified in real-time using a reservoir-based Recurrent Neural Network (RNN). The adaptation occurs online, while a disturbance force is repeatedly applied to the robot body.
Michele Folgheraiter +2 more
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Modeling Method of Human Motion Based on Dynamic Forest Model [PDF]
Jisuanji gongcheng, 2016 Aiming at the disadvantages that the existing modeling methods of human motion cannot be applied at the general nonlinear and non-Gaussian cases,based on the Markoff model,an improved modeling method of human motion is proposed.The Markov process of ...
SUN Li
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Effect of the COVID-19 pandemic on the number of deaths in Peru: 2017.03-2020.07
Semestre Economico, 2021 The objective of the research is to estimate the excess deaths during the COVID-19 epidemic in Peru. The methodology used for the ARMA models with structural with a structural change in mean. In the first place, the results show that the behavior of the
Rene-Paz Paredes
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Relay transmission under mobile edge computing in energy-limited networks with real-time constraints
Journal of Algorithms & Computational Technology, 2020 For energy-limited networks with real-time constraints, long-distance transmission, complex calculations, and limited delay are problems to be faced in service applications.
Guilu Wu +3 more
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, 2020 An enhanced method to determine the best-fit Auto-Regressive model (AR model) for structural damage identification is proposed in this paper. Whereby, two parameters of the model, including the number of model order and the window size of data, are ...
Nguyen, Andy +3 more
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Adaptive Importance Sampling Via Auto-Regressive Generative Models and Gaussian Processes
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 The quality of importance distribution is vital to adaptive importance sampling, especially in high dimensional sampling spaces where the target distributions are sparse and hard to approximate. This requires that the proposal distributions are expressive and easily adaptable. Because of the need for weight calculation, point evaluation of the proposal
Hechuan Wang +2 more
openaire +3 more sources
Healthcare Analytics, 2022 The COVID-19 series is obviously one of the most volatile time series with lots of spikes and oscillations. The conventional integer-valued auto-regressive time series models (INAR) may be limited to account for such features in COVID-19 series such as ...
Naushad Mamode Khan +5 more
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Direct and indirect self-tuning generalized minimum variance control [PDF]
Serbian Journal of Electrical Engineering, 2019 Theoretically, several self-tuning control (STC) algorithms have been developed and many simulation results have proved their feasibility in the past years, but applications of STC are hardly seen.
Kareem Hayder Jasim +3 more
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Spatiality in small area estimation: A new structure with a simulation study
Geospatial Health, 2020 In numerous practical applications, data from neighbouring small areas present spatial correlation. More recently, an extension of the Fay–Herriot model through the Simultaneously Auto- Rregressive (SAR) process has been considered.
Yadollah Mehrabi +3 more
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A Stochastic Dynamical Model of Slope Creep and Failure
Geophysical Research Letters, 2023 We propose a stochastic dynamical model to simulate slope secondary and tertiary creep phenomena. The slope secondary creep is represented by the Kesten process defined as a stochastic affine auto‐regressive process involving both multiplicative and ...
Qinghua Lei, Didier Sornette
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