Title :
A parallel analog signal processing unit based on radial basis function networks
Author :
Cancelo, Gustavo ; Mayosky, Miguel
Author_Institution :
Fermilab, Batavia, IL, USA
fDate :
6/1/1998 12:00:00 AM
Abstract :
This paper reports the design of an analog neuron circuit with Gaussian activation functions. The circuit is intended to be used for parallel computation of spatial distributed signals like the ones from array sensors (e.g. detectors) and images. The importance of the model is discussed in the context of Radial Basis Function and Regularization theory. Analog hardware implementation is performed as a natural approach for massive parallel computation of radial basis functions. Gaussian unit equations and simulation plots are provided along with an analysis of adjustable parameters
Keywords :
feedforward neural nets; high energy physics instrumentation computing; parallel algorithms; signal processing; Gaussian activation functions; Gaussian unit equations; adjustable parameters; analog neuron circuit; array sensors; massive parallel computation; parallel analog signal processing unit; parallel computation; radial basis function; radial basis function networks; radial basis functions; spatial distributed signals; Array signal processing; Circuits; Concurrent computing; Context modeling; Detectors; Distributed computing; Image sensors; Neurons; Sensor arrays; Signal processing;
Journal_Title :
Nuclear Science, IEEE Transactions on