Multisensory Memristive Circuits With Parallel Processing and Dual Adaptive Features

As the brain-like intelligence develops rapidly, it is urgent to design a more convenient and efficient control framework to cope with the challenge of processing multisensory signals in parallel. Therefore, a multisensory memristive circuit with dual adaptive, parallel processing, and multilevel reinforcement features is proposed. The circuit is mainly composed of modules for receptors, STM and LTM, attention, environmental monitoring and mutual associative memory. Automatic encoding of different sensorial signals is realised by the receptor modules. Dual adaptive regulation of the internal associative memory and external environmental changes on the circuit is implemented by modules of attention and environmental monitoring. Multilevel reinforcement memory is achieved through the interconnection of multiple dimensional features of the same objects. The process of encoding transformation of stimuli, experience memory, and feedback learning is automatically achieved in the brain-inspired neural network structure, which avoids the problems such as encoding difficulties during the conversion of the operating objects, and enables the realization of more brain-like intelligence. The circuit is applied to gripping and recognizing in robotic arms and the scenario memory of different production lines is simulated, which is promising for application in automated factories.