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DIGITAL Signal PROCESSING DIGITAL SIGNAL PROCESSING refers to manipulating analog information, such as sound or photographs that has been converted into a digital form. DSP also implies the use of a data compression technique. DSP refers to various techniques for improving the accuracy and reliability of digital communications. The theory behind DSP is quite complex. Basically, DSP works by clarifying, or standardizing, the levels or states of a digital signal. ADSP circuit is able to differentiate between human-made signals, which are orderly, and noise, which is inherently chaotic.

HISTORY OF Digital signal PROCESSING
Since the Second World War, if not earlier, technicians have speculated on the applicability of digital techniques to perform signal processing tasks. For example at the end of the 1940’s. Shannon, Bode and other researchers at the Bell Telephone Laboratories discussed the possibility of using digital circuit elements to implement filter functions. At this time, there was unfortunately no appropriate hardware available. Hence, cost, size and reliability strongly favored conventional, analog implementations.

During the middle of the 1950’s, Professor Linville at Massachusetts institute of Technology (MTI) discussed digital filtering at gratitude seminars. By then, control theory, based partly on works by Hurewiez had become established as a discipline, and sampling and its spectral effects were well understood. A number of mathematical tools, such as z-transform, which had existed since Laplace’s time, were now used in the electronics engineering community.
Technology at this point, however, was only able to deal with low-frequency control problems or low frequency seismic signal processing problems. While seismic scientists made notable use of digital filter concepts to solve problems, it was until the middle of the 1960s that a more formal theory of digital signal processing (DSP) began to emerge.

Application of digital signal

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