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摘要翻译：
Mamdani模糊模型是计算智能(CI)研究中的一项重要技术。在Mamdani模糊模型的背景下，提出了一种基于隶属度函数训练的监督学习方法。具体地，利用Mamdani技术对数码相机的自动变焦功能进行了建模。通过一系列仿真，验证了控制方法的性能，并给出了数值结果。
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英文标题：
《The Application of Mamdani Fuzzy Model for Auto Zoom Function of a
Digital Camera》
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作者：
I. Elamvazuthi, P. Vasant, J. F. Webb
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最新提交年份：
2010
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
Mamdani Fuzzy Model is an important technique in Computational Intelligence (CI) study. This paper presents an implementation of a supervised learning method based on membership function training in the context of Mamdani fuzzy models. Specifically, auto zoom function of a digital camera is modelled using Mamdani technique. The performance of control method is verified through a series of simulation and numerical results are provided as illustrations.
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PDF链接：
https://arxiv.org/pdf/1001.2279
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