Signal Processing

Signals are time - varying quantities which carry information. They may be, for example, audio signals (speech, music), images or video signals, sonar signals or ultrasound, biological signals such as the electrical pulses from the heart, communications signals, or many other types.

The basic idea is straightforward: Rather than design complex circuits to process signals, the signal is first converted into a sequence of numbers and processed via software.

Real time signal processing systems the result of the processing must be available within certain time constraints for it to be of use. If the result is not available in time, it may be of no use. For example, in developing a system which records the heart signal and looks for abnormalities, we may have a time frame of the order of seconds in which to react to any change in the signal pattern and to sound an alert.

DSP AND ITS APPLICATIONS

• Speech recognition provides a more natural interface to computer systems and information retrieval systems (such as telephone voice – response systems).

• Image recognition involves recognizing patterns in images, such as character recognition in scanned text or recognizing faces for security systems, and handwriting recognition.

• Image enhancement is the improvement of the quality of digital images, for example, when degraded by noise on a communications channel or after suffering degradation over time on older recording media.

• Audio enhancement and noise reduction is the improvement of audio quality, particularly in “ acoustically difficult ” environments such as vehicles. In cars and planes, for example, this is a desirable objective in order to improve passenger comfort and to enhance safety.

• Digital music in the entertainment industry uses special effects and enhancements — for example, adding three - dimensional sound “ presence ” and simulating reverberation from the surroundings.

• Communications and data transmission relies heavily on signal processing. Error control, synchronization of data, and maximization of the data throughput are prime examples.

• Biomedical applications such as patient monitoring are indispensable in modern medical practice. Medical image processing and storage continues to attract much research attention.

• Radar, sonar, and military applications involve detection of targets, location of objects, and calculation of trajectories. Civilian applications of the Global Positioning System (GPS) are an example of complex signal processing algorithms which have been optimized to operate on handheld devices.