Ultimate "SIR" in Autonomous Linear Networks with Symmetric Weight Matrices, and Its Use to Stabilize the Network - A Hopfield-like network

Abstract

In this paper, we present and analyse two Hopfield-like nonlinear networks, in continuous-time and discrete-time respectively. The proposed network is based on an autonomous linear system with a symmetric weight matrix, which is designed to be unstable, and a nonlinear function stabilizing the whole network thanks to a manipulated state variable called``ultimate SIR''. This variable is observed to be equal to the traditional Signal-to-Interference Ratio (SIR) definition in telecommunications engineering. The underlying linear system of the proposed continuous-time network is $\dot{\mathbf{x}}=\mathbf{B}\mathbf{x}$ where {\bf B} is a real symmetric matrix whose diagonal elements are fixed to a constant. The nonlinear function, on the other hand, is based on the defined system variables called ``SIR''s. We also show that the ``SIR''s of all the states converge to a constant value, called ``system-specific Ultimate SIR''; which is equal to $\frac{r}{{\lambda }_{max}}$ where $r$ is the diagonal element of matrix $\mathbf{B}$ and ${\lambda }_{max}$ is the maximum (positive) eigenvalue of diagonally-zero matrix $(\mathbf{B}-r\mathbf{I})$, where $\mathbf{I}$ denotes the identity matrix. The same result is obtained in its discrete-time version as well. Computer simulations for binary associative memory design problem show the effectiveness of the proposed network as compared to the traditional Hopfield Networks.

7 figures, submitted to IEEE Trans. on Circuits and Systems 1 (TCAS1) in Sep 2009