Recurrent Neural Network Topologies for Spectral State Estimation and Differentiation

Dölen, Melik
Lorenz, Robert


Recurrent Neural Network Topologies for Spectral State Estimation and Differentiation
Dölen, Melik; Lorenz, Robert D (2002-04-01)
Stochastic processes adapted by neural networks with application to climate, energy, and finance
Giebel, Stefan; Rainer, Martin (Elsevier BV, 2011-10-01)
Local climate parameters may naturally effect the price of many commodities and their derivatives. Therefore we propose a joint framework for stochastic modeling of climate and commodity prices. In our setting, a stable Levy process is drift augmented to a generalized SDE. The related nonlinear function on the state space typically exhibits deterministic chaos. Additionally, a neural network adapts the parameters of the stable process such that the latter produces increasingly optimal differences between si...
Stochastic assembly line balancing problems involving robots and reliability restriction
Şahin, Muhammet Ceyhan; Tural, Mustafa Kemal; Department of Industrial Engineering (2022-7-1)
When considering assembly processes in the manufacturing ecosystem, the task times may vary from cycle to cycle, especially in assembly lines where manual operations are abundant. Line stops, defective products, and off-line tasks caused by the uncertainty in assembly processes can be highly costly for companies. Stochastic assembly line balancing problems (SALBPs) consider the task processing times as random variables to deal with uncertainty in real-life assembly operations. The difficulties faced due to...
Stochastic Models Forpricing And Hedging Derivatives İn Incomplete Makets: Structure, Calibration, Dynamical Programming, Risk Optimization
Tezcan, Cihangir(2009-09-30)
THE PURPOSE AND THE RATIONALE (AMAÇ VE GEREKÇE) The common standard pricing methods of financial assets and derivative instruments determine the price as the fair value. The latter is defined as a unique arbitrage free price in a complete market. It is determined as expected value of the corresponding discounted payoff w.r.t. to a unique equivalent martingale measure (EMM). This method essentially relies on the assumption that that the market is complete, such that the buyer price and seller price match exa...
Stochastic modeling in computational electromagnetics by coordinate transformations
Özgün, Özlem; Kuzuoğlu, Mustafa (null; 2015-09-04)
Computational Electromagnetics (CEM) involves the process of modeling the interaction of electromagnetic fields with physical objects and environment through numerical solutions of Maxwell’s equations. The study of such interactions is crucial in the analysis and design of electromagnetic systems or devices. For example, in electromagnetic compatibility (EMC) applications, it is essential to characterize the immunity of devices to parasitic or intentional ele...
Citation Formats
M. Dölen and R. Lorenz, “Recurrent Neural Network Topologies for Spectral State Estimation and Differentiation,” 2000, vol. 10, Accessed: 00, 2021. [Online]. Available: