1. A recursive neural net, comprising: a block control unit for performing selection of a block to be updated and state updating therefor, thereby forming a recursive neural net including processing elements each having a linear saturated function as an input/output function, in which said processing elements are divided into a plurality of blocks, and states of said processing elements are asynchronously updated within each block, an optical computing unit for optically performing a vector matrix calculation, wherein a conversion given by A.sup.(k) below is performed on signals of x.sup.(j) (t+1) and x.sup.(j) (t): ##EQU19## where x=(x.sub.1. .. x.sub.i,. .. , X.sub.n).sup.T (0.ltoreq.x.sub.i .ltoreq.1) represents a state vector expressing a state of each individual neuron in said neural net, x.sup.(k) (k=1,. .. , m) represents a number m of subvectors expressing the states of said neurons included-in each of said blocks, and W.sub.kj represents a submatrix of synaptic weights matrix of a link connecting a j-th block to a k-th block; a threshold processing unit for performing a threshold processing operation, wherein a conversion given by B.sup.(k) below is preformed on the signals expressed by A.sup.(k) above: EQU B.sup.(k) =A.sup.(k) +.theta..sup.(k) where .theta..sup.(k) represents subvectors of a threshold vector EQU .theta.=[.theta..sup.(1)T, .theta..sup.(2)T,. .. , .theta..sup.(m)T ].sup.T ; a coefficient multiplying unit for performing a step-size processing operation, wherein a conversion given by C.sup.(k) below is performed on the signals expressed by B.sup.(k) above: EQU C.sup.(k) =.alpha..sub.k B.sup.(k) where .alpha..sub.k is a step-size for updating of the k-th block, and is set so as to satisfy the following expression: ##EQU20## a saturated linear computing unit for performing a saturated linear function operation, wherein a conversion given by D.sup.(k) below is performed on the signals expressed by C.sup.(k) above: D.sup.(k) =S(X.sup.(k) (t)+C.sup.(k)) where S is a non-linear operator causing a linear saturated function Sat to operate for each vector component: ##EQU21## wherein said updating is performed by a conversion as ABCD.