Introduction to Digital Signal Processing

The world of science and engineering is filled with signals: images from remote space probes, voltages generated by the heart and brain, radar and sonar echoes, seismic vibrations, and countless other applications. Digital Signal Processing (DSP) is the science of using computers to understand these types of data. It refers to various techniques for improving the accuracy and reliability of digital communications. The theory behind DSP is quite complex. DSP is primarily used to detect errors, and to filter and compress analog signals in transit. 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. Digital Signal Processors (DSP) take real-world signals like voice, audio, video, temperature, pressure, or position that have been digitized and then mathematically manipulate them. Signals need to be processed so that the information that they contain can be displayed, analyzed, or converted to another type of signal that may be of use. In the real-world, analog products detect signals such as sound, light, temperature or pressure and manipulate them. Converters such as an Analog-to-Digital converter then take the real-world signal and turn it into the digital format of 1’s and 0’s. From here, the DSP takes over by capturing the digitized information and processing it. It then feeds the digitized information back for use in the real world. It does this in one of two ways, either digitally or in an analog format by going through a Digital-to-Analog converter. All of this occurs at very high speeds. DSP is one of the most powerful technologies that will shape science and engineering in the twenty-first century. This text places the emphasis on understanding the principles and applications of DSP.