PCA and NMF subspace approaches have become the most representative methods in face recognition, which act in the similar way as a neural network auto-associative memory. By integrating with LDA subspace, in this paper, two subspace associative memories, PCA _LDA and NMF _LDA , are proposed, and how they recognize the partially damaged faces is presented. The theoretical expressions are plotted, and the comparative experiments are completed for the UMIST face database. It shows that NMF _LDA subspace associative memory outperform PCA _LDA subspace method significantly in recognizing partially damaged faces.