Abstract
Beta Basis Function Neural Networks (BBFNN) are powerful systems for learning and universal approximation characteristics. In this paper, we present a hardware implementation of the Beta neuron using the CMOS subthreshold-mode. We describe a low power low voltage analog Beta neuron circuit. Three main modules are used to realize the Beta function: a logarithmic current to voltage converter, a multiplier and an exponential voltage to current converter. Simulation results prove the validity of our neural hardware implementation. The control parameters of the Beta function are independent and are made easily by current sources. This analog implementation can be used easily to realize analog BBFNN.
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