PROCESSORS, DEVICES, SYSTEMS, AND METHODS FOR NEUROMORPHIC COMPUTING BASED ON MODULAR MACHINE LEARNING MODELS

摘要

The present disclosure discloses a method and a computing device for processing an input vector sequence to generate an output vector. The method comprises processing one or more input vectors of the input vector sequence to generate one or more sub-vectors respectively, the input vector sequence including a plurality of input vectors including the one or more input vectors arranged in a sequence, wherein the plurality of input vectors and the output vector characterize features of an object, and a respective input vector is processed by processing one or more input vectors adjacent to the respective input vector in the input vector sequence using a machine learning method to generate a corresponding sub-vector; and after sequentially generating the one or more corresponding sub-vectors for the one or more input vectors in the input vector sequence to form a sub-vector sequence including the one or more sub-vectors, generating the output vector based on the sub-vector sequence.