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Images matching based on a new gradient neural network

Focusing on the searching strategy in image matching, this paper constructs an energy function with features of a convex function based on Lyapunov Stability Theorem. It thus enables the Gradient neural network to converge steadily into the set of critical points of the target function. Then this paper tries to apply the network in image matching with moment invariants as the feature parameter. The specific steps of the experiments are supplied in this paper. According to the results of the experiments, this matching algorithm features good convergence, high speed, wide applicability and an extraordinary matching effect.