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Hong Wang

Researcher at Northeastern University (China)

Publications -  561
Citations -  10554

Hong Wang is an academic researcher from Northeastern University (China). The author has contributed to research in topics: Nonlinear system & Probability density function. The author has an hindex of 47, co-authored 510 publications receiving 8952 citations. Previous affiliations of Hong Wang include Zhejiang University & Shenyang Institute of Automation.

Papers
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Proceedings ArticleDOI

Minimum entropy control of non-Gaussian dynamic stochastic systems

TL;DR: This paper presents a new method to minimize the closed loop randomness for general dynamic stochastic systems using the entropy concept, using the linear B-spline model for the shape control of the system output probability density function.
Proceedings Article

Applying a novel extended Kalman filter to missile―target interception with APN guidance law: A benchmark case study

TL;DR: In this paper, an analytical recursive approach referred to as extended Kalman filter with unknown inputs without direct feedthrough (EKF-UI-WDF) is derived with the weighted least squares estimation for an extended state vector including states and unknown inputs which can be any type of signals without prior information.
Journal ArticleDOI

Robust Online Sequential RVFLNs for Data Modeling of Dynamic Time-Varying Systems With Application of an Ironmaking Blast Furnace

TL;DR: In order to solve the issue of modeling robustness when the dataset is contaminated with various outliers, a Cauchy distribution function weighted M-estimator is introduced to strengthen the robustness of the improved OS-RVFLNs.
Journal ArticleDOI

The study of joint input and state estimation with Kalman filtering

TL;DR: In this paper, the problem of joint input and state estimation for discrete-time stochastic systems with direct feedthrough from unknown inputs to outputs was investigated and a Kalman filter with unkno...
Journal ArticleDOI

Minimized Tracking Error Randomness Control for Nonlinear Multivariate and Non-Gaussian Systems Using the Generalized Density Evolution Equation

TL;DR: A new stochastic control algorithm is presented for nonlinear and non-Gaussian continuous-time systems based on the recently developed generalized density evolution equation, which is more tractable than the classical Liouville equation.