Introduction to Adaptive Signal Processing
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Transcript of Introduction to Adaptive Signal Processing
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ADAPTIVE SIGNAL
PROCESSINGTEXTBOOK : Adaptive Signal
Processing Bernard Widrow , S.D. Stearns
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COURSE OUTLINE Basic principles of adaptation Design explanation Operating characteristics Simpler forms of applications of
Adaptive Systems Methods of Physical Realization
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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
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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
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AREAS OF APPLICATIONS Fields of Communication Radar Sonar Seismology Mechanical Design Navigation Systems Biomedical Electronics
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GENERAL PROPERTIES Time varying Self – Adjustment Comparison between Fixed Design and
Adaptive Design Cannot be distinguished belonging to an
absolute clear subset
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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.
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OPEN LOOP ADAPTATION
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CLOSED LOOP ADAPTATION
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APPLICATIONS OF CLOSED LOOP ADAPTATION –
SIMPLE FORM OF CLOSED LOOP MODEL
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EXAMPLES OF ADAPTIVE SYSTEMS
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ADAPTIVE PREDICTOR
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ADAPTIVE LINEAR COMBINER
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INPUT SIGNAL AND WEIGHT VECTORS
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DESIRED RESPONSE AND ERROR