Digital signal processing(DSP) is the mathematical manipulation of an information signal to modify or improve it in some way. It is characterized by the representation of discrete time, discrete frequency, or other discrete domain signalsby a sequence of numbers or symbols and the processing of these signals.
The goal of DSP is usually to measure, filter and/or compress continuous real-world analog signals The first step is usually to convert the signal from an analog to a digital form, by samplingand then digitizing it using an analog-to-digital converter(ADC), which turns the analog signal into a stream of numbers. However, often, the required output signal is another analog output signal, which requires a digital-to-analog converter(DAC). Even if this process is more complex than analog processing and has a discrete value range, the application of computational power to digital signal processing allows for many advantages over analog processing in many applications, such as error detection and correctionin transmission as well as data compression. This course provides a good understanding of DSP principles and their implementation and equips the delegate to put the ideas into practice and/or to tackle more advanced aspects of DSP. 'Hands-on' laboratory sessions are interspersed with the lectures to illustrate the taught material and allow you to pursue your own areas of interest in DSP. The hands-on sessions use specially written software running on PCs.
Benefits
A comprehensive grounding in DSP concepts and algorithms plus practical information on the design and implementation of DSP systems.
Gives a good understanding of DSP principles and their implementation and equips the student to put the ideas into practice and/or to tackle more advanced aspects of DSP
The theoretical knowledge is illustrated by application examples, by demonstrations and by work in the laboratory.