Abstract: Efficiently simulating an Amari dynamics of a neural field a, the Amari dynamics being specified by the equation (1) where a(x,t) is the state of the neural field a, represented in a spatial domain (SR) using coordinates x,t, i(x,i) is a function stating the input to the neural field at time t, f[.] is a bounded monotonic transfer function having values between 0 and 1, F(x) is an interaction kernel, ? specifies the time scale on which the neural field a changes and h is a constant specifying the global excitation or inhibition of the neural field a. A method comprises the step of simulating an application of the transfer function f to the neural field a. Simulating an application of the transfer function f comprises smoothing the neural field a by applying a smoothing operator (S).

Abstract: A computer-implemented system and method for estimating properties of objects represented in digital images, comprising the steps of (a) encoding input data from a sensor in a neural map comprising neurons having numerical activation values, wherein the activation values in the neural maps have continuous time dynamics defined by an update scheme; (b) creating, adapting and deleting weights of the neural map in unsupervised, incremental manner; (c) transmitting data from an input map to an output map, based on the values of the weights; wherein each weight between the input map (IM) and a neural output map (OM) has a unique source and destination neuron; and wherein data transmission is directed; and (d) detecting correlations between the input map (IM).

Abstract: Efficiently simulating an Amari dynamics of a neural field (a), the Amari dynamics being specified by the equation (1) where a(x,t) is the state of the neural field (a), represented in a spatial domain (SR) using coordinates x,t, i(x,i) is a function stating the input to the neural field at time t, f[.] is a bounded monotonic transfer function having values between 0 and 1, F(x) is an interaction kernel, s specifies the time scale on which the neural field (a) changes and h is a constant specifying the global excitation or inhibition of the neural field (a). A method for simulating an Amari dynamics of a neural field (a), comprising the step of simulating an application of the transfer function (f) to the neural field (a). According to the invention, the step of simulating an application of the transfer function (f) comprises smoothing the neural field (a) by applying a smoothing operator (S).

Abstract: A computer-implemented system and method for estimating properties of objects represented in digital images, comprising the steps of (a) encoding input data from a sensor in a neural map comprising neurons having numerical activation values, wherein the activation values in the neural maps have continuous time dynamics defined by an update scheme; (b) creating, adapting and deleting weights of the neural map in unsupervised, incremental manner; (c) transmitting data from an input map to an output map, based on the values of the weights; wherein each weight between the input map (IM) and a neural output map (OM) has a unique source and destination neuron; and wherein data transmission is directed; and (d) detecting correlations between the input map (IM).