continuous-time model

Model Analysis of Fast Analogue Neural Circuit of Largest Value Signal Set Identification

An analysis of continuous-time model of high speed analogue K-winners-take-all (KWTA) neural circuit which is capable of identifying the K largest of unknown finite value N distinct inputs, where 1K N ≤ < is presented. The model is described by a state equation with discontinuous righthand side and by an output equation. Existence and uniqueness of the steady-states, convergence of state-variable trajectories and convergence time to the KWTA operation are analyzed. The model comparison with other close analogs is given.

Analogue neural circuit of largest magnitude signal set identification in unknown range

A continuous-time analogue neural circuit which is capable of identifying the K largest of unknown finite value N distinct inputs, where  , located in an unknown range is proposed. The circuit model is described by a state equation and by an output equation. A corresponding functional block diagram of the circuit is presented as N feed-forward hard-limiting neurons and two feedback neurons, which are used to determine the dynamic shift of inputs. The circuit combines such properties as high accuracy and speed, low hardware implementation complexity, and independency of initial conditions.