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This paper introduces KANalogue, a fully analogue implementation of Kolmogorov-Arnold Networks that uses negative-differential-resistance devices to perform learnable nonlinear functions directly in hardware. It achieves competitive accuracy with fewer parameters than analogue MLPs on MNIST, FashionMNIST, and CIFAR-10.