首页> 外国专利> ADAPTIVE STATE SPACE SIGNAL SEPARATION, DISCRIMINATION AND RECOVERY ARCHITECTURES AND THEIR ADAPTATIONS FOR USE IN DYNAMIC ENVIRONMENTS

ADAPTIVE STATE SPACE SIGNAL SEPARATION, DISCRIMINATION AND RECOVERY ARCHITECTURES AND THEIR ADAPTATIONS FOR USE IN DYNAMIC ENVIRONMENTS

机译:动态环境中的自适应状态空间信号分离,区分和恢复体系结构及其适应性

摘要

This invention unifies a set of statistical signal processing, neuromorphic systems, and microelectronic implementation techniques for blind separation and recovery of mixed signals. A set of architectures, frameworks, algorithms, and devices for separating, discriminating, and recovering original signal sources by processing a set of received mixtures and functions of said signals are described. The adaptation inherent in the referenced architectures, frameworks, algorithms, and devices is based on processing of the received, measured, recorded or otherwise stored signals or functions thereof. There are multiple criteria that can be used alone or in conjunction with other criteria for achieving the separation and recovery of the original signal content from the signal mixtures. The composition adopts both discrete-time and continuous-time formulations with a view towards implementations in the digital as well as the analog domains of microelectronic circuits. This invention focuses on the development and formulation of dynamic architectures with adaptive update laws for multi-source blind signal separation/recovery. The system of the invention seeks to permit the adaptive blind separation and recovery of several unknown signals mixed together in changing interference environments with very minimal assumption on the original signals. The system of this invention has practical applications to non-multiplexed media sharing, adaptive interferer rejection, acoustic sensors, acoustic diagnostics, medical diagnostics and instrumentation, speech, voice, language recognition and processing, wired and wireless modulated communication signal receivers, and cellular communications. This invention also introduces a set of update laws and links minimization of mutual information and the information maximization of the output entropy function of a nonlinear neural network, specifically in relation to techniques for blind separation, discrimination and recovery of mixed signals. The system of the invention seeks to permit the adaptive blind separation and recovery of several unknown signals mixed together in changing interference environments with very minimal assumption on the original signals.
机译:本发明统一了用于混合信号的盲分离和恢复的一组统计信号处理,神经形态系统和微电子实现技术。描述了通过处理一组接收到的信号的混合和功能来分离,区分和恢复原始信号源的一组架构,框架,算法和设备。所引用的体系结构,框架,算法和设备中固有的适配是基于对接收,测量,记录或以其他方式存储的信号或其功能的处理。有多种标准可以单独使用,也可以与其他标准结合使用,以实现从信号混合物中分离和回收原始信号含量。该组合物采用离散时间和连续时间两种形式,以期在微电子电路的数字域和模拟域中实现。本发明致力于具有自适应更新定律的动态体系结构的开发和制定,以用于多源盲信号分离/恢复。本发明的系统试图允许在变化的干扰环境中以对原始信号非常小的假设的自适应盲分离和恢复混合在一起的几个未知信号。本发明的系统在非多路复用媒体共享,自适应干扰抑制,声学传感器,声学诊断,医疗诊断和仪器,语音,语音,语言识别和处理,有线和无线调制通信信号接收器以及蜂窝通信中具有实际应用。 。本发明还引入了一组更新定律和相互信息的最小化以及非线性神经网络的输出熵函数的信息最大化,特别是涉及用于盲分离,区分和恢复混合信号的技术。本发明的系统试图允许在变化的干扰环境中以对原始信号非常小的假设的自适应盲分离和恢复混合在一起的几个未知信号。

著录项

  • 公开/公告号EP1088394B1

    专利类型

  • 公开/公告日2004-01-14

    原文格式PDF

  • 申请/专利权人 CLARITY LLC;

    申请/专利号EP19990928697

  • 发明设计人 ERTEN GAMZE;SALAM FATHI M.;

    申请日1999-06-16

  • 分类号H03H21/00;

  • 国家 EP

  • 入库时间 2022-08-21 22:56:54

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