analogue neural circuit

Using the analogue neural circuit of maximal value signals from signal set identification is proposed for information retrieval in data sets. The circuit is fast, it has simple structure and can be implemented in a modern hardware. A resolution of the circuit is theoretically infinite and it is not dependent on a value of its parameter. An average time necessary for trajectory convergence of the circuit state variable to a steady state is not dependent on a dimension of input data.

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.

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.

The problem of rank-order filtering is solved on the base of analogue neural circuit which determines maximal value signals among signal set. The filter is described by system of algebra-differential equations and combines such properties as high accuracy and speed, low computational and hardware implementation complexity, and independency on initial conditions. The filter can be used for processing of constant signals, variable signals, and also equal signals. The filter simulation examples confirming theoretical statements are provided.