Research on Adaptive Signal Processing Methods

自适应信号处理方法研究

• 批准号: 8904109
• 负责人: John Proakis
• 金额: $ 15.82万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-08-15 至 1992-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8904109&HistoricalAwards=false
• 关键词: Research; Adaptive; Signal; Processing; Methods

This research deals with the development, testing and mathematical analysis of adaptive signal processing algorithms based on higher-order statistics of the signals involved in the adaptation process and their applications. Different "criteria of goodness" in higher-order statistics domains and different adaptive filter realizations are being considered in the development of the new algorithms. Special emphasis is placed on the investigation of the numerical properties and performance of the algorithms. Performance metrics being considered include probability of error in the restored sequence as a function of SNR, sensitivity to signal statistics and data conditioning, rate of convergence, choice of sliding windows and finite work length effects. The performance of the new algorithms is compared to that of the existing ones to establish strengths and weaknesses. Finally, applications of the new algorithms are considered, e.g., in decision feedback equalization, in blind equalization, noise cancelling, and system identification.

本研究涉及的发展，测试和数学 高阶自适应信号处理算法分析 适应过程中涉及的信号的统计及其 应用. 高阶不同的“善的标准” 统计域和不同的自适应滤波器实现正在被 在新算法的开发中考虑。 特别强调 是放在调查的数值性质， 算法的性能。 正在考虑的绩效指标 包括作为以下函数的恢复序列中的错误概率 SNR、对信号统计和数据调节的灵敏度、 收敛性、滑动窗口的选择和有限工作长度效应。 新算法的性能进行了比较， 以确定优势和劣势。 最后， 考虑新算法的应用，例如，号决定 反馈均衡，在盲均衡，噪声消除，和 系统识别