DHGN network with mode-based receptive fields for 2-dimensional binary pattern recognition

We introduce an extension to existing Distributed Hierarchical Graph Neuron (DHGN) network for 2-dimensional binary pattern recognition. The new form of DHGN network, termed as receptive field DHGN network (RF-DHGN) is a hybrid of a receptive field layer for 2D feature extraction, and one or more DHGN subnets for feature recognition. All inputs to the network, in the form of synaptic weights are automatically determined through mode-based activation function within the RF neurons. The proposed scheme minimizes the need for large number of neurons as compared to the normal DHGN scheme. Furthermore, the results of preliminary recognition tests indicate high recognition accuracy, similar to existing DHGN approach for distributed pattern recognition