Adaptive processing with neural network controlled resonator-banks

The author describes a novel neuromorphic architecture for structurally adaptive control systems. The neural network controlled resonator-bank (NCRB) architecture consists of two main components, a resonator-bank filter structure and a neural network which controls the transfer characteristics of the filter. The architecture offers an attractive alternative to the approximation of nonlinear dynamic systems having a finite number of stable operating points with quasi-linear behavior. The first results of the experimental analysis of the NCRB structure are encouraging. The system is apparently able to approximate a wide range of nonlinear dynamic behaviors