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Titlebook: Advances in Intelligent Signal Processing and Data Mining; Theory and Applicati Petia Georgieva,Lyudmila Mihaylova,Lakhmi C Jain Book 2013

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樓主: 大腦
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發(fā)表于 2025-3-25 05:12:02 | 只看該作者
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發(fā)表于 2025-3-25 10:18:49 | 只看該作者
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發(fā)表于 2025-3-25 13:35:43 | 只看該作者
A Sequential Monte Carlo Method for Multi-target Tracking with the Intensity Filter,y in simulations but also in real world applications. In addition it can be shown that the performance of the PHD filter decreases substantially if the a priori knowledge of the clutter intensity is chosen incorrectly.
24#
發(fā)表于 2025-3-25 17:55:03 | 只看該作者
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發(fā)表于 2025-3-25 20:26:49 | 只看該作者
Reinforcement Learning with Neural Networks: Tricks of the Trade,y for one to understand how to apply reinforcement learning using a neural network. Additionally, we describe two example implementations of reinforcement learning using the board games of Tic-Tac-Toe and Chung Toi, a challenging extension to Tic-Tac-Toe.
26#
發(fā)表于 2025-3-26 00:36:34 | 只看該作者
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28#
發(fā)表于 2025-3-26 08:39:39 | 只看該作者
https://doi.org/10.1007/978-3-319-45805-2t agents based exclusively on their observed trajectories.We use these as building blocks for developing a unified tracking and behavioral reasoning paradigm. Both synthetic and realistic examples are provided for demonstrating the derived concepts.
29#
發(fā)表于 2025-3-26 14:44:59 | 只看該作者
Advances in Intelligent Signal Processing and Data MiningTheory and Applicati
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發(fā)表于 2025-3-26 18:33:50 | 只看該作者
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