Subject: Architecture for Knowledge-Based Signal Processing

From: Brian Evans <[email-masked]>
Date: Mon, 27 Feb 1995 12:48:20 -0800

Special Digital Signal Processing Seminar
Monday, March 6, 1995 1:00 - 2:00 pm
Hogan Room, 531 Cory Hall

"Anatomy of IPUS: A View Inside an Architecture for 
Knowledge-Based Signal Processing"

Joseph M. Winograd
Knowledge-Based Signal Processing Laboratory
Dept. of Electrical, Computer, and Systems Engineering
Boston University

Abstract

Knowledge-based techniques can be applied within any signal processing
system which must make context-dependent decisions about signal processing 
actions.  Candidate tasks for knowledge-based processing range in scope 
from the small, such as determining which of several pitch-detection 
algorithms will give (or has given) the most reliable output, to the highly 
complex, as in the separation and identification of multiple sound sources 
in an acoustic scene.  Difficulties encountered in applying the classical 
dataflow model of signal processing systems to the design of knowledge-based 
systems have led to the development of alternative architectures, such as 
the AI-inspired IPUS (Integrated Processing and Understanding of Signals).
The IPUS architecture represents a radical departure from dataflow, offering
a global hierarchical blackboard in lieu of fixed data paths.  It also
incorporates a sophisticated control planner which performs both strategic
and opportunistic scheduling of processing actions according to modular and
hierarchical control schema.  This talk will describe the major components
of the IPUS architecture, focusing on their practical ramifications for the
incorporation of knowledge-based techniques into modern signal processing
system design.  An IPUS-based system for the analysis of radar clutter
will be demonstrated.