Digital Signal Processing Reference
In-Depth Information
Adaptive Filters
Adaptive structures
•
The linear adaptive combiner
•
The least mean squares (LMS) algorithm
•
Programming examples for noise cancellation and system identification using
C code
•
Adaptive filters are best used in cases where signal conditions or system parame-
ters are slowly changing and the filter is to be adjusted to compensate for this
change. A very simple but powerful filter is called the
linear adaptive combiner
,
which is nothing more than an adjustable FIR filter. The LMS criterion is a search
algorithm that can be used to provide the strategy for adjusting the filter coeffi-
cients. Programming examples are included to give a basic intuitive understanding
of adaptive filters.
7.1 INTRODUCTION
In conventional FIR and IIR digital filters, it is assumed that the process parame-
ters to determine the filter characteristics are known. They may vary with time, but
the nature of the variation is assumed to be known. In many practical problems,
there may be a large uncertainty in some parameters because of inadequate prior
test data about the process. Some parameters might be expected to change with
time, but the exact nature of the change is not predictable. In such cases it is highly
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