Adaptive processing with neural network controlled resonator-banks

A structurally adaptive processing system that can dynamically change its transfer characteristics as a response to changes in the environment is described. The neural network controlled resonator-bank architecture consists of two main components, a resonator-bank filter structure and a neural network that controls the transfer characteristics of the filter. The architecture offers an attractive alternative for the approximation of time-variant nonlinear dynamics having a finite number of stable operating points with quasi-linear characteristics.<
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