This paper presents a new approach to develop Field Programmable Analog Arrays (FPAAs). It is based on a simple current-mode primitive which allows easy adaptability to implement the fundamental analog functions such as integration, attenuation and amplification. A novel solution to avoid the use of excessive number of programming devices in the signal path is proposed. The paper also introduces an architecture for the FPAA, which is devoid of the conventional switching and connection modules used in Field Programmable Gate Arrays (FP-GAS). High frequency operation, a simple programming methodology, operation over almost three decades of frequency (30kHz to lOMHz), and use of standard digital CMOS fabrication process are the salient features of the proposed FPAA. We have demonstrated the feasibility of the FPAA by implementing some signal processing functions.

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A radial basis function network (RBFX) circuit for function approximation is presented. Simulation and experimental results show that the nehvork has good approximation capabilities. The RBFN was a squared hyperbolic secant with three adjustable parameters amplitude , width and center. To test the network a sinusoidal and sinc function was approximated.

This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.

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