According　to　the　weight　design　problem　of　discrete　Hopfield　neural　network(DHNN),　an　improved　learning　algorithm　for　weight　design　is　proposed.　On　the　basis　of　the　dynamic　analysis　for　DHNN,　the　learning　algorithm　is　designed.　The　orthogonal　matrix　is　got　by　using　the　method　of　matrix　decomposition(MD),　and　the　orthogonal　matrix　is　used　to　get　the　weight　matrix　of　DHNN　directly.　The　weight　matrix　which　is　obtained　by　the　learning　algorithm　can　store　information　well,　so　that　the　testing　sample　can　converge　to　a　stable　point.　The　learning　algorithm　does　not　need　block　calculation.　The　calculation　steps,　the　amount　of　calculation　and　the　number　of　iterations　are　reduced,　so　the　operating　speed　of　the　network　is　improved.　Finally,　the　algorithm　is　applied　to　water　quality　evaluation　to　prove　its　effectiveness　and　feasibility.