This invention discloses a multi-
physical quantity collaborative sensing neuromorphic
synaptic device and its dynamic environment
adaptive method, relating to the fields of neuromorphic synaptic devices and multi-
physical quantity sensing technology. It includes: a multi-
physical quantity sensing layer, comprising a temperature-sensitive unit, a
humidity-sensitive unit, and a gas-sensitive unit; a
memristor synaptic modulation layer; a collaborative
control unit; a read / write control module; and an interface and integration module. All of the above structures are integrated onto a wearable carrier, achieving hardware-level
collaboration between multi-physical quantity sensing and
memristor synaptic weight control. This invention achieves accurate identification of interference types and differentiated anti-interference
processing through dynamically updated interference source features combined with a lightweight
machine learning classifier, overcoming the shortcomings of existing technologies such as fixed filtering thresholds, lack of dynamic interference feature libraries, and difficulty in coping with various interferences in complex environments. Simultaneously, by dynamically adjusting the
feature matching threshold and the minimum threshold, the probability of
clutter misjudgment is reduced.