Signal Processing based on parameter Structural Modeling and Separation of Highly correlated Signals of Known Structure

摘要

Results incd the study of signal processing based on the use of parameter structural modeling (PSM) are presented. First, we introduce a special form of time-series modeling based on signal-dependent building blocks. Such modeling is used in the design of a nested- form transversal structure, known as a composite filter, based on a shift-invariant finite impulse resonse (FIR) as well as infinite impulse response (IIR) building blocks. The newly proposed composite PSM model (CPSM) possesses a unique feature, namely, its ability to suppress one signal of a given structure, while at the same time being ideally transparent to another one.