Radial basis function networks with quantized parameters
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A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. The results indicate that the network presents good approximation capability even with severe quantization. The parameter quantization decreases the memory size and circuit complexity required to store the network parameters leading to compact mixed-signal circuits proper for low-power applications. ©2008 IEEE.
How to cite this document
Lucks, Marcio B.; Nobuo, Oki. Radial basis function networks with quantized parameters. CIMSA 2008 - IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings, p. 23-27. Available at: <http://hdl.handle.net/11449/70591>.
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