| Summary: | Application of existing Temporal Convolutional Network(TCN) to temporal sequence prediction results in a large amount of computation and redundant parameters,and therefore it is not applicable to mobile terminals with limited computing capabilities and storage space,including mobiles phones,tablets,and laptops.To address the problem,this paper proposes a Lightweight TCN(L-TCN).The network replaces the common convolution in TCN with depthwise separable convolution.The channel convolution is used to implement separation of common convolution on a spatial dimension,so as to broaden the network and extend the scope of feature extraction.Then the pointwise convolution is used to simplify the computation of common convolution operations.Experimental results show that compared with TCN,the proposed L-TCN can significantly reduce the number of parameters and the amount of calculation of network models while keeping the precision of the temporal sequence prediction,which demonstrates it is applicable to mobile terminals with limited computing capabilities and storage space.
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