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This paper proposes Full-Parallel Convolutional Neural Networks (FP-CNN) for specific target recognition, which utilize the analog memristive array circuits to carry out the vector-matrix multiplication, and generate multiple output feature maps in one single processing cycle. Compared with ReLU and Tanh function, we adopt the absolute activation function innovatively to reduce the network scale dramatically, which can achieve 99% recognition accuracy rate with only three layers. Furthermore,doi:10.1587/elex.16.20181034 fatcat:3d7oqzepgrdv7l4ezx2ajzh2bm