Radiation source signal identification method of improved particle swarm extreme learning machine

The invention discloses a radiation source signal identification method of an improved particle swarm extreme learning machine. The method comprises the following steps of S1, preprocessing a radiation source signal; S2, extracting characteristic parameters of the preprocessed signal obtained in the step S1, and obtaining a training sample and a test sample; S3, putting the training sample obtained in the step S2 into an extreme learning machine, initializing parameters of a particle swarm optimization algorithm, and obtaining a learning factor value by an exponential function method; and S4, through learning of the extreme learning machine in the step S3, calculating a mean square error as a moderate value and inertia weight division, continuously updating the speed and the position of the particles, and adjusting the connection weight and a threshold value of the extreme learning machine. The method mainly solves a problem that a traditional optimized extreme learning machine is not high in classification p