In　this　paper,　a　fast　algorithm　for　vector　autoregressivemoving-average　(ARMA)　parameter　estimation　under　noise　environments　is　proposed.　Based　on　an　equivalent　AR　parameter　model　technique　and　a　Yule-Walker　equation　technique,　solving　the　parameter　estimation　problem　of　the　VARMA　model　is　well　converted　into　solving　linear　equations.　Therefore,　the　proposed　algorithm　has　a　lower　computational　complexity　and　a　faster　speed　than　conventional　algorithms.　Application　examples　with　application　to　Lorenz　systems　confirm　that　the　proposed　algorithm　can　obtain　a　good　solution.