remove missing values from matrix or data frame

Is there any way besides looping to remove complete rows from a matrix 
or data frame where there is at least one NA in any of the columns?

For example

 > a

       [,1]     [,2]
  [1,] 0        2.6875
  [2,] 8.366667 6.625
  [3,] 15.6     4.375
  [4,] 23.4     6.25
  [5,] 29       5.09375
  [6,] 18       NA
  [7,] 0        4.15625
  [8,] 9.366667 6.25
  [9,] 14.73333 5.875
 [10,] 31.26667 6.15625
 [11,] NA       2.357
 [12,] NA       5.4234
 [13,] 0        3.34375
 [14,] 7.666667 2.78125
 [15,] NA       NA

In a, rows 6, 11, 12, and 15 should be removed.

na.omit(a) does nothing, nor does na.omit(as.data.frame(a)).  I can get 
a matrix of which are NA and not by "i<-!is.na(a)", but this doesn't 
seem to help ("a[i]" isn't the thing I'm after).

I know I am missing something simple and standard, but I haven't been 
able to see it yet (nor on Google).

Thanks.