Introduction to Adaptive Signal Processing

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ntroduction to Adaptive Signal Processing

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ADAPTIVE SIGNAL

PROCESSINGTEXTBOOK : Adaptive Signal

Processing Bernard Widrow , S.D. Stearns

COURSE OUTLINE Basic principles of adaptation Design explanation Operating characteristics Simpler forms of applications of

Adaptive Systems Methods of Physical Realization

INTRODUCTION Definition of Adaptation/ Adaptive Systems

Systems with capability to adapt. Adapt : - To make suitable changes for certain

conditions or requirements Or To adjust or modify fittingly

Common examples of Adaptive Systems :- Nervous System in living beings with cognitive functions

Theoretical Definition : An adaptive automaton is a system whose structure is alterable or adjustable in such a way that its behavior or performance improves through contact with its environment. Eg:- AGC in Radio

CHARACTERISTICS OF ADAPTIVE SYSTEMS Self Optimize Trainable Self – Designing Behavior Extrapolation Self repairable – adapt to internal

defects Non-Linear Systems with time varying

parameters Complex and Difficult to Analyze Increased system performance

AREAS OF APPLICATIONS Fields of Communication Radar Sonar Seismology Mechanical Design Navigation Systems Biomedical Electronics

GENERAL PROPERTIES Time varying Self – Adjustment Comparison between Fixed Design and

Adaptive Design Cannot be distinguished belonging to an

absolute clear subset

SPECIAL FEATURES OF ADAPTIVE SYSTEM

Adaptive systems are adjustable – depends on finite-time average signal characteristics rather than on instantaneous values of signals or instantaneous values of internal system states.

Adjustments of adaptive systems are changed purposefully in order to optimize specified performance measures.

OPEN LOOP ADAPTATION

CLOSED LOOP ADAPTATION

APPLICATIONS OF CLOSED LOOP ADAPTATION –

SIMPLE FORM OF CLOSED LOOP MODEL

EXAMPLES OF ADAPTIVE SYSTEMS

ADAPTIVE PREDICTOR

ADAPTIVE LINEAR COMBINER

INPUT SIGNAL AND WEIGHT VECTORS

DESIRED RESPONSE AND ERROR