Signal Processing Review

Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency.

Digital signal processing and analog signal processing are subfields of signal processing. DSP applications include audio and speech processing, sonar, radar and other sensor array processing. 

DSP can involve linear or nonlinear operations. Nonlinear signal processing is closely related to nonlinear system identification and can be implemented in the time, frequency, and spatio-temporal domains.The most important thing that this lab taught me was the difference between a DSP processor and a general processor. Most general purpose microprocessors are present in personal computers. They are often used for computation, text editing, multimedia display, and communication over a network. Other microprocessors are part of embedded systems. These provide digital control over practically any technology, such as appliances, automobiles, cell phones, industrial process control, etc.
The DSP processor, on the other hand, is a particular type of microprocessor. DSP stands for digital signal processing. It is basically any signal processing that is done on a digital signal or information signal. A DSP processor is a specialized microprocessor that has an architecture optimized for the operational needs of digital signal processing. DSPs also tend to be two to three times as fast as general-purpose microprocessors. This is because of architectural differences. DSPs tend to have a different arithmetic Unit architecture; specialized units, such as multipliers, etc. In this lab we have extensively used code composer studio for making the programs.Some of the programs we based on the concepts that we learnt from last semester in signals and systems. After completing this practical lab I have understood the importance of DSP and how it is used in applications such as audio signal processing, audio compression, digital image processing, video compression, speech processing, speech recognition, digital communications, digital synthesizers, radar, sonar, seismology and bio medicine.

In the beginning of every practical we had to  get the targets for that lab from sir and perform it . The progress after the lab session was monitored and if the work was not complete sir didn't give his signature. The experiments has to be submitted online on MOODLE. Overall it was a good experience to learn this course.