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This paper establishes methodology for the robust
and stable design of infinite impulse response (IIR) digital
filters using hybrid differential evolution method. Differential
Evolution (DE) is undertaken as a global search technique
and exploratory search is exploited as a local search technique.
DE is a population based stochastic real parameter
optimization technique relating to evolutionary computation,
whose simple yet powerful and straight forward features make
it very attractive for numerical optimization. Exploratory
search aims to fine tune the solution locally in promising
search area. This proposed DE method augments the capability
to explore and exploit the search space locally as well globally
to achieve the optimal filter design parameters by applying
the opposition learning strategy and random migration. A
multivariable optimization is employed as the design criterion
to obtain the optimal stable IIR filter that minimizes the
magnitude approximation error and ripple magnitude. DE
method is implemented to design lowpass, highpass, bandpass,
and bandstop digital IIR filters. The achieved design of
IIR digital filters by applying DE method authenticates that
its results are comparable to other algorithms and can be
effectively applied for higher filter design.
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