Implementing Universal CNN Neuron

The universal CNN neuron can realize arbitrary Boolean functions including both linearly separable Boolean functions (LSBF) and linearly not separable Boolean functions (non-LSBF). However, determining the optimal (or near-optimal) orientation vector and the parameters in the multi-nested discriminant function contained within a universal CNN neuron is still a difficult task. By the aid of the DNA-like learning algorithm proposed a few years ago on the feedforward binary neural networks, the bottleneck problem can be solved if the number of input variables is

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