The neuron's nonlinear model - multidimensional spline

A new neuron-s model is described, which "synapses" are spline-transformators of entrance signals, "soma" calculates a weighed summary of transformated signals and "axon" executes a multipurpose spline-transformation. The main points - abscissas of splines are set in equiprobable intervals and ordinates are calculated with an iterational algorithm of the steepest descent adopted to splines.

The analogue of the neuron-s spline-model is a multidimensional orthogonal spline, which forming and directing surfaces are one-dimensional splines providing for clear interpretation of modeled causal relationships.

The neuron-s spline-model works with incomplete input data, provides for high exactitude of the model operation, its multiresolution is equivalent to three-layer network of known neurons - models.