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Titlebook: Optimal Firm Behaviour in the Context of Technological Progress and a Business Cycle; Onno Hilten Book 1991 Springer-Verlag Berlin Heidelb

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11#
發(fā)表于 2025-3-23 12:24:29 | 只看該作者
Onno van Hiltento analyze their computation complexity and compare their performance. Then it summarizes suitable scenes for these networks and concludes key points that should be concerned when constructing an attention network. Last it points out some future directions of the attention network.
12#
發(fā)表于 2025-3-23 16:27:42 | 只看該作者
13#
發(fā)表于 2025-3-23 19:08:42 | 只看該作者
14#
發(fā)表于 2025-3-24 01:42:38 | 只看該作者
Models with a Business Cycle,d by a fluctuating demand curve. This leads to another kind of dynamics: the model is . (see p.46). In a non-autonomous model it is difficult to apply the path connecting procedure and the existence of a decision rule is doubtful.
15#
發(fā)表于 2025-3-24 05:57:53 | 只看該作者
Book 1991mists may be, when it comes to extending or modifying the existing theory to make it applicable to a certain economic problem, an understanding of optimal control theory (which is the mathematical theory used in this thesis, ovh) based solely on heuristic arguments will often turn out to be inadequa
16#
發(fā)表于 2025-3-24 09:13:37 | 只看該作者
17#
發(fā)表于 2025-3-24 13:12:32 | 只看該作者
cessing speed is required more strictly in order to guarantee the service quality. Mobile edge computing technology makes the server closer to the terminal and assists the terminal to process data nearby, bringing better user experience. In mobile edge computing system, most terminal devices have st
18#
發(fā)表于 2025-3-24 18:26:16 | 只看該作者
Onno van Hiltenlike defenses such as firewalls, intrusion detection, and anti-virus software, honeynet is a more proactive and deceptive defense. This paper addresses the specific design and implementation challenges of honeynets by proposing an innovative approach that leverages a dynamic Human-Machine Interface
19#
發(fā)表于 2025-3-24 19:35:43 | 只看該作者
20#
發(fā)表于 2025-3-25 01:07:58 | 只看該作者
Onno van Hilteny and smart homes. However, existing WiFi sensing methods have certain limitations, including inadequate denoising, susceptibility of selected features to environmental influences, and low recognition accuracy. In this paper, we propose a WiFi-based Human Identification method called WiHI, which uti
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