The invention relates to the technical field of
digital signal processing, and provides an MIP LED light
color compensation driving method and device based on
deep learning. The method comprises the following steps: acquiring real-
time data of an MIP
LED array, preprocessing the real-
time data, and generating a multi-
modal data
tensor formed by standard data; performing decoupling
processing on the data
tensor by constructing a decoupling network to generate a decoupling component; performing
volt-
ampere characteristic modeling based on
product data of the MIP
LED array to generate
volt-
ampere characteristic parameters, and generating compensated driving
voltage according to the decoupling component and the
volt-
ampere characteristic parameters; and performing fusion
processing on the driving
voltage and a driving
signal in the real-
time data to generate a
control signal. Real-time data containing driving signals and the like are firstly obtained, brightness and other components are separated through decoupling processing, compensation driving
voltage is generated in combination with hardware volt-ampere characteristics, finally, control signals are generated through fusion, and the stability, accuracy and uniformity of light color output of the MIP
LED array are effectively improved.