EEE 311: Digital Signal Processing-I
Course Teacher: Dr. Newaz Md. Syfur Rahim
Dept of EEE, BUET, Dhaka 1000.
Syllabus: As mentioned in your course calendar
1. Digital Signal Processing: Principles, Algorithms, and Applications – John G. Proakis 2. Digital Signal Processing: A Practical Approach – Emmanuel C. Ifeachor 3. Schaum’s Outlines of Digital Signal Processing
4. Modern Digital Signal Processing – Roberto Cristi
This course will cover Chapter 1 through 5 of Proakis’s and Chapter 5 through 7 of Ifeachor’s book.
Signals Systems and Signal Processing
A signal is a function of one or more independent variables that usually represent time and/ or space. A signal contains some kind of information that can be conveyed, displayed, or manipulated. Examples of signals of particular interests are: * Speech, which we encounter in telephony, radio, and everyday life. * Biomedical signals, such as electrocardiogram
* Sound and music, such as reproduced by CD player
* Video and image, which people watch on television
* Radar signals, which are used to determine the range and bearing of distant targets A system is a practical device that performs an operation on a signal to modify the signal or extract additional information from it. A system may be electrical, mechanical, thermal, hydraulic or an algorithm. By signal processing we mean the type of operations that is performed by the system to the signal. Digital signal processing is concerned with the digital representation of signals and the use of digital processors to analyze, modify, or extract information from signals. The signals used in most DSP are derived from analog signals which have been sampled at regular intervals and converted into a digital form. DSP is now used in many areas where analog methods were previously used and in applications which are difficult or impossible with analog method. Advantages of DSP
The main attractions of DSP are due to the following advantages: * Digital signal can withstand channel noise and distortion much better than analog signal. * Repeaters can be used for long distance digital communication * Digital system can be easily modified with software that implements the specific applications. * Digital signals can be coded to reduce error rate.
* Storage of digital signal is easy and inexpensive and does not deteriorate with age. * Reproduction of digital messages is extremely reliable without distortion * DSP allows sophisticated applications such as speech recognition and image compression to be implemented with low power portable devices * The accuracy is only determined by the number of bits used. * No drift in performance with temperature or age
* Linear phase response can be achieved and complex adaptive filtering algorithms can be implemented using DSP techniques. DSP designs can be expensive when large bandwidth signals are involved. The ADCs/ DACs may not have sufficient resolution for wide bandwidth DSP applications. In some DSP systems if an insufficient number of bits are used to represent variables serious degradation in system performance may result. Applications of DSP
DSP has revolutionized many areas of science and engineering. They are summarized below: * Measurements and analysis: Preconditioning the measured signal by rejecting the disturbing noise and interference. The digital filters can be found in ECG and EEG equipment to record the weak signals in the presence of heavy background noise and interference. DSP techniques are also used for the analysis of radar and sonar echoes. In most GPS receivers today advanced DSP techniques are employed to enhance resolution and reliability. [+ patient monitoring, X-ray storage, enhancement] * Telecommunications: DSP is used in telephone systems for DTMF (dual-tone multi-frequency) signaling, echo cancelling of telephone...
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