The implementation of a nonlinear wave metric for image analysis and classification on the 64/spl times/64 I/O CNN-UM chip

In this paper the implementation of a nonlinear wave metric on the 64/spl times/64 I/O CNN-UM chip and its experimental results are presented. The nonlinear wave metric was designed and introduced as a generalized theorem for object analysis and classification. This proposed metric includes the well-known distance measures such as Hamming, Hausdorff metrics as special cases. The defined computational method is well-suited for cellular neural network (CNN) architecture and the experimental results shows good correlation with theoretic considerations.