Generation of a biometrically activated digital signature based on hybrid neural network algorithms

This paper suggests a model of a hybrid wide neural network based on perceptrons, quadratic form networks and multidimensional difference and hyperbolic Bayes functionals. It is experimentally proved that this model is highly efficient when used for biometric authentication and generation of a digital signature activated biometrically. The paper suggests methods of generating keys of a digital signature and personal authentication by handwritten patterns, a key stroke manner and facial parameters. Comparatively high rates of reliability for taken solutions were achieved that were estimated taking into account the variability of dynamic biometric patterns over time.