Array signal processing with interconnected Neuron-like elements

Estimation of angles of arrival of plane waves from data observed at an array of sensors is performed with a network of interconnected, instantaneous, saturating non-linear elements called neurons. The networks use the observed data to decide which among a large number of hypothesized angles of arrivals best fits the data. A possible stochastic-digital implementation of such a network is also indicated.

[1]  I. Reed,et al.  Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[2]  Sergio Telles Ribeiro,et al.  Random-Pulse Machines , 1967, IEEE Trans. Electron. Comput..

[3]  Avinash C. Kak,et al.  Array signal processing , 1985 .

[4]  H. T. Kung.  Why systolic architectures? , 1982, Computer.

[5]  J. Goodman,et al.  Neural networks for computation: number representations and programming complexity. , 1986, Applied optics.

[6]  T. Kailath,et al.  VLSI and Modern Signal Processing , 1984 .

[7]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Brian R. Gaines,et al.  Stochastic computing , 1967, AFIPS '67 (Spring).

[10]  B. Widrow,et al.  Adaptive antenna systems , 1967 .