Digital signals form almost all of the data analyzed by computer science engineers and scientists. Digital signals made up of images, text, sound and other types now belong to the domain of computer science, electrical and electronic engineering.
Digital signal processing involves the mathematical processing of information signals for modifying or improving them. It represents discrete time and frequency.
The objective behind digital signal processing or dsp is to calibrate, filter or compress the continual real-world analog signals. The signal is first converted from analog to digital and then it is digitized through an analog to digital converter. This converter converts the analog signal into a series of numbers.
The final output is an analog signal which is received after using a digital to analog converter. Digital signal processing may be more complicated than analog processing, but the use of computational power enables several advantages over analog processing in most applications.
The main advantages include detecting and correcting errors during transmission and data compression.
The applications of dsp include:
Digital image processing
Statistical signal processing
Sensor array processing
Sonar/radar signal processing
Audio/speech signal processing
Signal processing for controlling systems, for communications, biomedical and seismic data processing among others.
The signal processing algorithms run on digital signal processors, standard computer systems and specially developed hardware like application specific integrated circuit.
The latest technologies involved in digital signal processing include powerful microprocessors, digital signal controllers, gate arrays and stream processors. Based on requirements, the signal processing tasks could be implemented on standard computers and in embedded processors that could include digital signal processors.