An Extended Generalized Prandtl-Ishlinskii Hysteresis Model for I2RIS Robot [0.03%]
一种扩展的广义普拉尼什金滞后的I2RIS机器人模型研究
Yiyao Yue,Mojtaba Esfandiari,Pengyuan Du et al.
Yiyao Yue et al.
Retinal surgery requires extreme precision due to constrained anatomical spaces in the human retina. To assist surgeons achieve this level of accuracy, the Improved Integrated Robotic Intraocular Snake (I2RIS) with dexterous capability has ...
Learning Approximate Symbolic Solutions to Burgers' Equation using Symbolic Regression [0.03%]
使用符号回归学习Burgers方程的近似解析解
Benjamin G Cohen,Burcu Beykal,George M Bollas
Benjamin G Cohen
This work explores the application of symbolic regression to learn symbolic solutions to Burgers' equation without data. We demonstrate a stepwise symbolic regression strategy that explores models that provide tractable logic from coordinat...
Reza Vafaee,Milad Siami
Reza Vafaee
Formulating state estimation for a large-scale, discrete-time, linear time-invariant system as a least-squares problem can be computationally challenging as the problem dimensions increase with time. Recently, randomized sampling has demons...
Identifying the dynamics of interacting objects with applications to scene understanding and video temporal manipulation [0.03%]
交互式场景理解与视频编辑中的动态物体识别算法研究
Armand Comas,Christian Fernandez,Sandesh Ghimire et al.
Armand Comas et al.
There is an ongoing effort in the machine learning community to enable machines to understand the world symbolically, facilitating human interaction with learned representations of complex scenes. A pre-requisite to achieving this is the ab...
Arya Honarpisheh,Rajiv Singh,Jared Miller et al.
Arya Honarpisheh et al.
This paper considers the problem of non-parametric identification of low-order models from time-domain experimental data using a combination of Caratheodory Fejer and Loewner-based interpolation, followed by a Loewner matrix Balanced Reduct...
Rajiv Singh,Tianyu Dai,Mario Sznaier et al.
Rajiv Singh et al.
We consider the problem of identification of time-varying, and nonlinear systems from measurements of its inputs and outputs over a chosen time frame. We present the rational maps in the time, frequency, and correlation domain as an effecti...
Benjamin P Russo,Daniel A Messenger,David Bortz et al.
Benjamin P Russo et al.
Operator theoretic methods in dynamical system have been dominated by the use of Koopman operators and their continuous time counterparts, such as Koopman Generators and Liouville Operators. The advantage gained from their use primarily ste...
Joshua Pickard,Cooper Stansbury,Amit Surana et al.
Joshua Pickard et al.
In this paper we consider aspects of geometric observability for hypergraphs, extending our earlier work from the uniform to the nonuniform case. Hypergraphs, a generalization of graphs, allow hyperedges to connect multiple nodes and unambi...
Robustly Linearized Model Predictive Control for Nonlinear Infinite-Dimensional Systems [0.03%]
非线性无穷维系统的鲁棒线性化模型预测控制
Hamza El-Kebir,Richard Berlin,Joseph Bentsman et al.
Hamza El-Kebir et al.
This work presents a computationally efficient approach to robustly linearized model predictive control for nonlinear affine-in-control evolution equations on infinite-dimensional system state. In this setting, robust linearization refers t...
Kernel-Based Particle Filtering for Scalable Inference in Partially Observed Boolean Dynamical Systems [0.03%]
基于核的粒子过滤在部分观察布尔动态系统中的可扩展推理中的应用
Mohammad Alali,Mahdi Imani
Mohammad Alali
This paper addresses the inference challenges associated with a class of hidden Markov models with binary state variables, known as partially observed Boolean dynamical systems (POBDS). POBDS have demonstrated remarkable success in modeling...