RBF circuits based on folded cascode differential pairs

• Autor(a) principal: Lucks, Marcio Barbosa [UNESP]
• Data de Publicação: 2008
• Outros Autores: Oki, Nobuo [UNESP]
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1145/1404371.1404402; http://hdl.handle.net/11449/70689
• topic: Artificial neural networks; Folded cascode topology; Radial basis function; Differential pairs; Gaussian; Output currents; Signal conditioning; SPICE simulations; Telemetry systems; Aircraft; Attitude control; Backpropagation; Feedforward neural networks; Functions; Image segmentation; Integrated circuits; Medical imaging; Networks (circuits); Neural networks; Probability density function; Spacecraft; SPICE; Systems analysis; Topology; Trellis codes; Radial basis function networks

We propose new circuits for the implementation of Radial Basis Functions such as Gaussian and Gaussian-like functions. These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode configuration. We also propose a multidimensional version based on the unidimensional circuits. SPICE simulation results indicate good functionality. These circuits are intended to be applied in the implementation of radial basis function networks. One possible application of these networks is transducer signal conditioning in aircraft and spacecraft vehicles onboard telemetry systems. Copyright 2008 ACM.