Applications of Fuzzy Systems to Signal Processing

模糊系统在信号处理中的应用

• 批准号: 9122018
• 负责人: Jerry Mendel
• 金额: $ 20.28万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-04-15 至 1995-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9122018&HistoricalAwards=false
• 关键词: Applications; Fuzzy; Systems; Signal; Processing

Mendel In many practical signal processing problems, information is often represented in two forms: one is a set of input-output data pairs, obtained by measuring the outputs of the system for some typical input signals; and, the other is a set of linguistic descriptions about the system, often in the form of IF-THEN fuzzy rules, from human experts who are very familiar with the behavior of the system. This research is developing a general method to combine both numerical input/output pairs and linguistic IF-THEN rules into signal processing system design within the framework of fuzzy system theory. The objectives are to: 1. theoretically justify the practical successes of fuzzy systems; 2. develop synthesis methods for fuzzy systems which use both numerical and linguistic information; and 3. apply these synthesis methods to signal processing problems, such as time-series prediction, and subject these methods to theoretical performance analyses. An optimal design method for fuzzy systems which will match given input-output pairs to arbitrary accuracy is also being developed.

孟德尔 在许多实际的信号处理问题中，信息通常以两种形式表示：一种是通过测量某些典型输入信号的系统输出而获得的一组输入-输出数据对;另一种是关于系统的一组语言描述，通常以IF-THEN模糊规则的形式，来自非常熟悉系统行为的人类专家。本研究在模糊系统理论的架构下，发展出一种将数值输入/输出对与语言IF-THEN规则结合的联合收割机方法。 目标是：1. 从理论上证明模糊系统的实际成功; 2. 发展模糊系统的综合方法，使用数字和语言信息; 3. 将这些综合方法应用于信号处理问题，如时间序列预测，并对这些方法进行理论性能分析。 模糊系统的优化设计方法，将匹配给定的输入输出对任意精度也正在开发中。