Inspired by the recent developments in data sciences,we introduce an intrinsic sparse mode decomposition method for high dimensional random fields.This sparse representation of the random field allows
In this paper we discuss the concept of weak solution for a new type of mean-field stochastic differential equations,which drift coefficient depends on the full past of the state but also on the law o
Few existing models produce reasonable market dynamics of volatility smile.The challenge is that volatility processes are usually specified to generate smile effects,rather than to produce maturity co
The energy management of engine waste heat recovery system is a complex problem characterized by great coupling,large inertia and uncertain delay.A commander-tracker energy management framework was pr
The Extended State Observer(ESO),which is featured with timely estimating the “total disturbance"of system,has been proven to be powerful dealing with nonlinear uncertain systems.With the idea of ESO,
We propose a fast method to approximate the real structured stability radius of a linear dynamical system with output feedback when real perturbations bounded with respect to the Frobenius norm are co
In this talk,the robust stability analysis for linear implicit m-th order difference equations is discussed.We allow the leading coefficient coefficient to be singular,i.e.,we include the situation th
In the drug development arena,the rapid accumulation of new quantitative methodologies and tools pushed the emergence of systemic and mechanistic studies of pharmacology that drive the drug R&D.
Ambulatory blood pressure measurement(ABPM)is superior to the traditional single blood pressure(BP)measurements.In this talk,we discussed an R package: Gabpm based on the previous work to model and vi