SAR Target Recognition Based on Cholesky Decomposition Weighted Kernel Extreme Learning Machine

Abstract

An SAR target recognition algorithm based on extreme learning machine is proposed. The traditional extreme learning machine cannot overcome the problem of sample noise and imbalance. To solve the problem, this paper introduces the weighted extreme learning machine algorithm, and uses KFCM algorithm combined with the proportion of samples to obtain the sample weight matrix. At the same time, in view of the problem that ordinary extreme learning machine uses matrix inverse to train the process, a calculation method based on choleksy decomposition is proposed. The experimental results show that the algorithm in this paper is faster and has higher recognition rate than ordinary algorithms such as KELM, SVM and BP neural network.