Apparatus and method for using analog circuits to embody non-lipschitz mathematics and properties using attractor and repulsion modes

Abstract

A network of coupled neurons for implementing Non-Lipschitz dynamics for modeling nonlinear processes or conditions comprising: a plurality of neurons, each being configurable in attractor and repulsion modes of operation, and programmable by an external signal; a plurality of synaptic connections for connecting at least a portion of the plurality of neurons for passage of data from one neuron to another; feedback circuitry for incrementing and decrementing an analog voltage output depending upon the output of the synaptic connection; whereby by the circuit solves Non-Lipschitz problems by programmably controlling the attractor and repulsion modes. A method of programming a network for solving Non-Lipschitz problems comprising providing a plurality of neurons, each programmable into a plurality of modes including repulsion and attraction modes; interconnecting the plurality of neurons using synaptic connections; providing feedback to at least one of the neurons; whereby by programming the neurons Non-Lipschitz terminal dynamics can be achieved.

Dependencies are inferred from the claim text.