Results 31 to 40 of about 152,517 (290)
Complexity, 2021 Cognitive searching optimization is a subconscious mental phenomenon in decision making. Aroused by exploiting accessible human action, alleviating inefficient decision and shrinking searching space remain challenges for optimizing the solution space ...
Bingxuan Ren, Tangwen Yin, Shan Fu
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A Semi-Markov Modulated Interest Rate Model
, 2012 In this paper we propose a semi-Markov modulated model of interest rates. We assume that the switching process is a semi-Markov process with finite state space E and the modulated process is a diffusive process.
D'Amico, Guglielmo +2 more
core +1 more source
IEEE Access, 2019 This paper investigates the H∞ consensus of linear multi-agent systems with semi-Markov switching network topologies and measurement noises. The information that each agent measures its neighbors's has multiplicative noises.
Meiyan Cong, Xiaowu Mu
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IEEE Access, 2021 In this work, the problem of finite-time asynchronous fault detection filter design is investigated for conic-type nonlinear semi-Markovian jump systems with time delay, missing measurements and randomly jumping fault signal.
V. Nithya +3 more
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A semi-Markov model for price returns
, 2011 We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday return are described by a discrete time homogeneous semi-Markov process and the overnight returns ...
D'Amico, Guglielmo, Petroni, Filippo
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Structure and Randomness of Continuous-Time Discrete-Event Processes
, 2017 Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process.
Crutchfield, J. P., Marzen, S. E.
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Markovian perturbation, response and fluctuation dissipation theorem [PDF]
, 2010 We consider the Fluctuation Dissipation Theorem (FDT) of statistical physics from a mathematical perspective. We formalize the concept of "linear response function" in the general framework of Markov processes.
Dembo, Amir, Deuschel, Jean-Dominique
core +3 more sources
AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Estimating Incentive and Welfare Effects of Non-Stationary Unemployment Benefits [PDF]
The distribution of unemployment duration in our equilibrium matching model with spell-dependent unemployment benefits displays a time-varying exit rate.
Andrey Launov, Klaus Wälde
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A semi-Markov model with memory for price changes
, 2011 We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday returns are described by a discrete time homogeneous semi-Markov which depends also on a memory ...
D’Amico G Petroni F +3 more
core +1 more source