Results 41 to 50 of about 30,326 (205)
Controlling Dynamical Systems Into Unseen Target States Using Machine Learning
Advanced Intelligent Systems, EarlyView.Parameter‐aware next‐generation reservoir computing enables efficient, data‐driven control of dynamical systems across unseen target states and nonstationary transitions. The approach suppresses transient behavior while navigating system collapse scenarios with minimal training data—over an order of magnitude less than traditional methods.
Daniel Köglmayr +2 more
wiley +1 more source
Weak Subdifferential in Nonsmooth Analysis and Optimization
Journal of Applied Mathematics, 2011 Some properties of the weak subdifferential are considered in this paper. By using the definition and properties of the weak subdifferential which are described in the papers (Azimov and Gasimov, 1999; Kasimbeyli and Mammadov, 2009; Kasimbeyli and ...
Şahlar F. Meherrem, Refet Polat
doaj +1 more source
Melnikov analysis in nonsmooth differential systems with nonlinear switching manifold
, 2018 We study the family of piecewise linear differential systems in the plane with two pieces separated by a cubic curve. Our main result is that 7 is a lower bound for the Hilbert number of this family.
Bastos, Jéfferson L. R. +3 more
core +1 more source
Biotechnology and Bioengineering, EarlyView.ABSTRACT Adeno‐associated viral (AAV) vectors for gene therapy are becoming integral to modern medicine, providing therapeutic options for diseases once deemed incurable. Currently, viral vector purification is a critical bottleneck in the gene therapy industry, impacting product efficacy and safety as well as accessibility and cost to patients ...
Kelvin P. Idanwekhai +9 more
wiley +1 more source
Non-smooth analysis method in optimal investment-BSDE approach
Advances in Difference Equations, 2018 In this paper, the investment process is modeled by backward stochastic differential equation. We investigate a necessary condition for optimal investment problem by the method of non-smooth analysis.
Helin Wu, Yong Ren, Feng Hu
doaj +1 more source
Optimal error estimates of a mixed finite element method for\ud parabolic integro-differential equations with non smooth initial data [PDF]
, 2010 In this article, a new mixed method is proposed and analyzed for parabolic integro-differential equations (PIDE) with nonsmooth initial data. Compared to mixed methods for PIDE, the present method does not bank on a reformulation using a resolvent ...
Goswami, D., Pani, A. K., Yadav, S
core
Error estimates for a semidiscrete finite element method for fractional order parabolic equations
, 2012 We consider the initial boundary value problem for the homogeneous time-fractional diffusion equation $\partial^\alpha_t u - \De u =0$ ($0< \alpha < 1$) with initial condition $u(x,0)=v(x)$ and a homogeneous Dirichlet boundary condition in a bounded ...
Jin, Bangti, Lazarov, Raytcho, Zhou, Zhi
core +2 more sources
Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges
Biotechnology and Bioengineering, EarlyView.ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz +3 more
wiley +1 more source
Differential-Algebraic Equations and Beyond: From Smooth to Nonsmooth Constrained Dynamical Systems [PDF]
, 2018 The present article presents a summarizing view at differential-algebraic equations (DAEs) and analyzes how new application fields and corresponding mathematical models lead to innovations both in theory and in numerical analysis for this problem class ...
Kleinert, Jan, Simeon, Bernd
core +1 more source
Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization
, 2017 Stochastic composition optimization draws much attention recently and has been successful in many emerging applications of machine learning, statistical analysis, and reinforcement learning.
Gu, Bin +3 more
core +1 more source