The present invention belongs to the field of mode identification and brain-like machine learning, specifically relates to an information processing method, system and apparatus based on a context signal prefrontal-lobe-like network, and aims to solve the problems of a complex system structure, a poor flexibility and a large demand for training samples in a complex situation, i.e. in a complex multi-task situation. The method of the present invention comprises: selecting a corresponding feature vector extractor to carry out feature extraction; carrying out dimensional matching on an information feature vector and each context signal in a context signal set; and inputting a context feature vector after dimensional matching into a feature vector classifier to obtain classification information. In the method of the present invention, multi-task learning for context information is realized by means of a module similar to a prefrontal lobe, mapping dependent on context information can be gradually learnt when the context information cannot be determined in advance, and processed data can be applied to multi-task learning or continuous multi-task learning with a higher requirement.
INFORMATION PROCESSING METHOD, SYSTEM AND APPARATUS BASED ON CONTEXT SIGNAL PREFRONTAL-LOBE-LIKE NETWORK