Signals are a very fundamental part of every telecommunication system, and
such systems abound with examples of signal processing techniques. In recent
years more and more attention has been given to the use of digital signal
processing techniques in telecommunication systems. For many applications
information is now most conveniently recorded, transmitted and stored in
digital form. As a result, digital signal processing is becoming an
important modern tool. Typical reasons for signal processing include:
estimation of characteristic signal parameters, elimination or reduction
of unwanted interference and transformation of a signal into a form that is
in some sense more informative. Digital signal processing deals with the
representation of signals as ordered sequences of numbers and the processing
of those sequences. Digital signals are those for which both time and
amplitude are discrete.
Before we go in for Digital signal processing we need to know why we are
going for it when we know we have analog signal processing. The prime benefit
of Digital signal processing over analog signal processing is flexibility.
In general, a digital processing system, is more easily reconfiguredi, as
parameters of the problem change. In fact, digital simulations are now
frequently used to analyze designs in an attempt to identify potentially
costly design errors before the hardware is built. Applications for digital
signal processing currently exist in diverse fields such as accoustics,
sonar, radar, geophysics, communications and medicine.
A category of digital
signal processing known as adaptive signal processing is a relatively new
area in which applications are increasing rapidly. Adaptive signal processing
evolved from techniques developed to enable the adaptive control of time-
varying systems. It has gained a lot of popularity due to the advances in
digital technology that have increased the computing capacities and
broadened the scope of digital signal processing. The key difference between
classical signal processing techniques and adaptive signal processing
method is that in the latter we deal with time varying digital systems.
When adaptive filters are used to process non-stationary signals, whose
statistical properties vary in time, the required amount of a prior
information is often less than that required for processing via fixed
digital filters.