Three Dimensional Heteroassociative Hopfield Model

Recognition of three dimensional object is always an interesting subject. Neural network model with its associative capability is an important approach to solving such complex problem. This paper puts forward a heteroassociative Hopfield model in matrix form, which can deal with recognition of three dimensional object with a much smaller interconnection matrix than the original Hopfield model. Thus, this result should be interesting for the development of neural newtork models and for practical applications.