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4 days ago · Abstract. Reinforcement learning (RL) excels in optimizing policies for discrete-time Markov decision processes (MDP). However, various systems are inherently ...
4 days ago · The effect of noise from the plasma power transmission is analyzed and modeled by a two-state Markov model. The noise is characterized, and by using a cost ...
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5 days ago · Link to Paper Search Results by DOI. Survivability Analysis for a Wireless Ad Hoc Network Based on Semi-Markov Model, IEICE TRANSACTIONS ON INFORMATION AND ...
Missing: Burstiness | Show results with:Burstiness
2 days ago · To this end, this paper proposes a hierarchical multimodal deep learning model (HMMED) for malicious encrypted traffic detection. This model adopts the ...
Missing: Burstiness | Show results with:Burstiness
5 days ago · A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and ...
Missing: Burstiness | Show results with:Burstiness
3 days ago · Namely, the model uses a discrete-time Markov chain embedded over continuous time to capture a fixed end-to-end congestion window, a carrier sense protocol ...
Missing: Burstiness | Show results with:Burstiness
5 days ago · ... simulations, which use stochastic (random) ... time slot could be covered with a presentation ... networks into the optical domain, creating optical neural networks ...
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3 days ago · Harmonic retrieval techniques are the foundation of radio channel sounding, estimation and modeling. This paper introduces a Deep Learning approach for joint ...
1 day ago · ... Simulations, and Games (Security and Professional ... Time Square | The Shift (Volume 1)|Mr S W Lothian ... (Model)|Sa Neal Coordinance to Freedom|Kathleen ...
5 days ago · A Neural Network Model ... Continuous versus Discrete Time Modeling in Growth and Business Cycle Theory ... Markov Chain Models in Practice: A Review of Low Cost ...