to describe the function in the big-oh in simplest terms the seven functions listed in section are the most common functions used in conjunction with the big-oh notation to characterize the running times and space usage of algorithms indeedwe typically use the names of these functions to refer to the running times of the algorithms they characterize sofor examplewe would say that an algorithm that runs in worst-case time log as quadratic-time algorithmsince it runs in ( time likewisean algorithm running in time at most log would be called linear-time algorithm big-omega just as the big-oh notation provides an asymptotic way of saying that function is "less than or equal toanother functionthe following notations provide an asymptotic way of saying that function grows at rate that is "greater than or equal tothat of another let (nand (nbe functions mapping nonnegative integers to real numbers we say that (nis ohm( ( )(pronounced " (nis big-omega of ( )"if (nis ( ( )that isthere is real constant and an integer constant > such that ( >=cg( )for > this definition allows us to say asymptotically that one function is greater than or equal to anotherup to constant factor example nlog is ohm( log njustification log > log nfor > big-theta in additionthere is notation that allows us to say that two functions grow at the same rateup to constant factors we say that (nis th ( ( )(pronounced " (nis big-theta of ( )"if (nis ( ( )and (nis ohm( ( )that isthere are real constants and ' and an integer constant > such that ' (nn example log log isth( log njustification log