Patent ID: 11922296
Assignee: RAIN NEUROMORPHICS INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A network, comprising:
plurality of inputs;
a plurality of outputs;
a plurality of hardware neurons;
a plurality of nodes between the plurality of inputs and the plurality of outputs, the plurality of nodes including a plurality of hidden nodes, a portion of the plurality of hidden nodes being coupled with the plurality of hardware neurons, a portion of the network having an analytic solution computable by modified nodal analysis (MNA) using an MNA solution matrix, at least one submatrix of the MNA solution matrix being at least one symmetric solution submatrix, connections between the plurality of hidden nodes being configured such that a gradient of a loss function for the network explicitly is calculatable using the at least one symmetric solution submatrix, the at least one symmetric solution submatrix describing the connections and corresponding to the connections being reciprocal with respect to the plurality of outputs; and
a plurality of weights for the plurality of hidden nodes, the plurality of weights being coupled with the connections, the plurality of weights including a plurality of programmable impedances coupled between at least a portion of the plurality of nodes, the plurality of programmable impedances being programmable based on the gradient of the loss function by perturbing a plurality of states of the plurality of outputs, measuring a plurality of resulting perturbations in at least one electrical characteristic for the connections, and programming the plurality of programmable impedances based on the plurality of resulting perturbations in the at least one electrical characteristic, the connections being between the portion of the plurality of hidden nodes and the plurality of weights;
wherein the measuring the resulting perturbations for the connections corresponds to measuring the gradient for the plurality of weights.