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New trends in intelligent system design for embedded and measurement applications

机译:嵌入式和测量应用智能系统设计的新趋势

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摘要

Intelligent systems adopt soft-computing techniques (encompassing neural networks, fuzzy logic, genetic algorithms, and expert systems) to solve complex problems by mimicking human reasoning. On the other hand, conventional algorithmic approaches are extremely powerful and efficient in tackling applications for which a procedural solution can be easily defined. By themselves, each of these techniques may be the optimal solution for a subproblem, but not efficient enough to solve the problem as a whole. Composite systems, consisting of conventional and soft-computing components in cooperation, are now more than a promise to face complex application needs. In this article we present recent advances in the design of composite systems, with specific reference to embedded and measurement applications.
机译:智能系统采用软计算技术(包括神经网络,模糊逻辑,遗传算法和专家系统)通过模仿人类推理来解决复杂问题。另一方面,常规算法方法在处理容易定义程序解决方案的应用程序中非常强大和高效。这些技术本身可能是一个子问题的最佳解决方案,但效率不足以整体解决问题。组合系统由协作的常规和软计算组件组成,现在已有望满足复杂的应用程序需求。在本文中,我们介绍了复合系统设计的最新进展,特别是针对嵌入式和测量应用程序。

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