The function of a receiver in a binary Communication system is to distinguish between two transmitted signals (or) () in the presence of noise.

The performance of Receiver is usually measured in terms of the probability of error P_{e} an the receiver is said to be optimum if it yields the minimum probability of error.

i.e, optimum receiver is the one with minimum probability of error P_{e} .

optimum receiver takes the form of Matched filter when the noise at the receiver input is white noise.

**optimum receiver (or) optimum filter:-**

The block diagram of optimum receiver is as shown in the figure below

the decision boundary is set to .

**Probability of error of optimum filter:-**

The probability of error can be obtained as similar to Integrate and dump receiver. Here we will consider noise as Gaussian Noise.

The output of optimum filter is .

The output of sampler is

suppose if Binary ‘1’ is transmitted then the input is , to find the probability of error this transmitted ‘1’ should be received as ‘0’.

this is possible when the condition is true.

1 will be received as 0 .

.

similarly a Binary ‘0’ will be received as ‘1’ if and only if

.

.

.

the conditions are summarized in the table

Noe the Probability Distribution Function of Gaussian noise with zero mean and standard deviation is given by

.

Probability of error= probability ‘1’ will be received as ‘0’ =probability ‘0’ will be received as ‘1’.

area under the curve (or) area under the curve .