Is there a way to vectorize this for loop to speed up?

Hello

Is there a way to vectorize this for loop to speed up?

thank you

       for j =1 :size(Rond_Input2Cell,1)

            for k=1: size(Rond_Input2Cell,2)

                Rond_Input2Cell(j,k)=  (Pre_Rond_Input2Cell(j,k)*Y_FGate(k))+(net_Cell(k)*Y_InGate(k)*tmp_input(j)) ;

            end
        end

Matrixs size:

Rond_Input2Cell =39*120

Pre_Rond_Input2Cell = 39*120

Y_FGate=1*120 (row vector)

net_Cell=1*120 (row vector)

Y_InGate =1*120 (row vector)

tmp_input =1*39 (row vector)

Answer 1

[Andrei Bobrov]

for j = 1 : size(R,1)
    for k = 1 : size(R,2)
        R(j,k)=  (PR(j,k)*YF(k))+(C(k)*YI(k)*t(j)) ;
    end
end

Matrixs size:

R =39*120

PR = 39*120

YF=1*120 (row vector)

C=1*120 (row vector)

YI =1*120 (row vector)

t =1*39 (row vector)

solution:

R = bsxfun(@times,PR,YF) + t(:)*(C.*YI)

[armita mani]

thanks for your answer, but when I run it I get this error "Matrix dimensions must agree." In your solution what do bsxfun? would you please guide me?

thank you

[Andrei Bobrov]

1) About bsxfun.

2)

>> R = rand(39,120);%39*120

>> PR = rand(39,120);%39*120

>> YF = rand(1,120);%1*120 (row vector)

>> C = rand(1,120);%1*120 (row vector)

>> YI = rand(1,120);%1*120 (row vector)

>> t = rand(1,39);%1*39 (row vector)

>> R = bsxfun(@times,PR,YF) + t(:)*(C.*YI);

no errors

[armita mani]

thank you, Is there another replacement way without bsxfun, for example like second part "t(:)*(C.*YI)"?

[Andrei Bobrov]

"t(:)*(C.*YI)"?

only for vectors (column and rows) and for @times. Example:

>> a = 1:5

a =

     1   2   3   4   5

>> b = 10:10:40
b =

     10   20   30   40

>> a(:)*b
ans =

      10    20    30    40
      20    40    60    80
      30    60    90   120
      40    80   120   160
      50   100   150   200

>>