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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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Tianjing Wang, Lanyong Zhang and Sheng Liu
Robust nonlinear filtering is an important method for tracking maneuvering targets in non-Gaussian noise environments. Although there are many robust filters for nonlinear systems, few of them have ideal performance for mixed Gaussian noise and non-Gauss...
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Forough Moosavi, Hamid Shiri, Jacek Wodecki, Agnieszka Wylomanska and Radoslaw Zimroz
In this paper, a novel method for long-term data segmentation in the context of machine health prognosis is presented. The purpose of the method is to find borders between three data segments. It is assumed that each segment contains the data that repres...
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Li Ma, Ning Cao, Xiaoliang Feng and Minghe Mao
In view of the fact that indoor positioning systems are usually affected by non-Gaussian noise in complex indoor environments, this paper tests the data in the actual scene and analyzes the distribution characteristics of noise, and proposes a new indoor...
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Ioannis Tsoukalas, Simon Michael Papalexiou, Andreas Efstratiadis and Christos Makropoulos
Since the prime days of stochastic hydrology back in 1960s, autoregressive (AR) and moving average (MA) models (as well as their extensions) have been widely used to simulate hydrometeorological processes. Initially, AR(1) or Markovian models with Gaussi...
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