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反问题和正问题是成对出现的。通常,学术界将已知原因(输入)、过程(模型)而探求结果(输出)的一类问题称为正问题。与此相对应,就有了两种反问题:已知模型、输出求未知输入的“溯源”问题和已知输入、输出来反求模型(或模型参数)的系统辨识问题。在现实社会和人类生活中,反问题无处不在;在关系国家命脉的经济生产和国防军事领域中反问题更是随处可见。例如,与人类健康福祉密切相关的无痛无损伤、在体表进行测量的医学诊...
The focus of this talk is on the numerical methods used to identify parameters in partial differential equations. Typically, an optimization approach is used to solve this class of inverse problems, w...
Optimal control, reinforcement learning and other optimization-based methods have been widelyapplied to control synthesis for real systems in physics, biology and robotics. However, in many complicate...
Researchers have discovered a novel way to perform “general inverse design” with reasonably high accuracy. This breakthrough paves the way for further development of a burgeoning and fast-moving field...
This paper deals with the problem of the electromagnetic linear inverse scattering from magnetic anomalies buried in a lossy half space, for a scalar and two dimensional case. First, the formulation ...
In what follows, we explore the general relationship between eye gaze during a category learning task and the information conveyed by each member of the learned category. To understand the nature of t...
The inverse design of a three-dimensional nanophotonic resonator is presented. The design methodology is computationally fast (10 minutes on a standard desktop workstation) and utilizes a 2.5-dimensio...
The Maximum Likelihood Estimator (MLE) is most often used to estimate the signal time delay in a multipath en vironment. There are various implementations of the MLE which can be divided into the time...
We consider a model problem of recovering a function f(x1, x2) from noisy Radon data. The function f to be recovered is assumed smooth apart from a discontinuity along a C2 curve – i.e. an edge. We us...
The peculiar properties of the Inverse Weibull (IW) distribution are shown. It is proven that the IW distribution is one of the few models having upside- down bathtub (UBT) shaped hazard function. Thr...
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
A global stochastic search method, which is strictly derivative-free yet directed through a gain-based additive update term, is proposed and applied to the inverse problem of ultrasound modulated opti...
Regularized kernel methods such as support vector machines (SVM) and support vector regression (SVR) constitute a broad and flexible class of methods which are theoretically well investigated and comm...
In a recent paper Birke and Bissantz (2008) considered the problem of nonparametric estimation in inverse regression models with convolution-type operators. For multivariate predictors nonparametric m...
The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The pa...

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