Further studies dynamic neural networks and fuzzy logic with applications to neuro-control and neuro-vision systems in robotics

进一步研究动态神经网络和模糊逻辑及其在机器人神经控制和神经视觉系统中的应用

• 批准号: 5625-2011
• 负责人: Gupta, Madan
• 金额: $ 1.6万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=544274
• 关键词: Further; studies; dynamic; neural; networks

Dynamic neural networks and fuzzy logic are the two recently developing theoretical tools which have found a wide range of applications in the areas such as control of complex dynamic systems, vision systems, robotics, medical image processing, and decision making problems in industrial systems. Over the past two decades, our group at the Intelligent Systems Research Laboratory has developed an extensive theoretical basis in these two important areas, have merged these two mathematical tools for developing the fuzzy neural systems and have applied these theoretical tools to problems of complex dynamic systems. Over the next five years, we wish to extend these theoretical tools in the field of dynamic neural networks and fuzzy neural systems, and apply them to some industrial, medical image processing and space problems.

动态神经网络和模糊逻辑是最近开发的两个理论工具，这些工具在控制复杂的动态系统，视觉系统，机器人技术，医疗图像处理以及工业系统中的决策问题等领域中发现了广泛的应用。在过去的二十年中，我们的智能系统研究实验室的小组在这两个重要领域建立了广​​泛的理论基础，并合并了这两种数学工具来开发模糊的神经系统，并将这些理论工具应用于复杂的动态系统问题。在接下来的五年中，我们希望将这些理论工具扩展到动态神经网络和模糊神经系统领域，并将其应用于某些工业，医学图像处理和空间问题。