lec1 DSP.pdf

Eng. Aden Hassan Lecture one This lecture serves as an introduction to the course and is intended to provide an indication of the importance and scope of the field of digital signal processing. Content:  Introduction to digital signal processing  Discrete-Time Signals and Systems  Sha...

Eng. Aden Hassan Lecture one This lecture serves as an introduction to the course and is intended to provide an indication of the importance and scope of the field of digital signal processing. Content:  Introduction to digital signal processing  Discrete-Time Signals and Systems  Shannon’s sampling theorem  Analog to digital converter  Time and frequency domain representation of discrete time signals  Z-transform and inverse z-transform  Introduction to the Fourier transform and discrete time Fourier transform  Discrete Fourier transform & Fast Fourier transform  Design of FIR and IIR filters  This course assumes a previous exposure to signal and system. Including linear system theory for continuous-time signals and systems including Fourier and Laplace Transforms.  Alan V. Oppenheim , Discrete time-signal Processing, prentice hall; 3rd edition, 2009.  Luis F. Chaparro, Signals and Systems Using MATLAB, Department of Electrical and Computer Engineering University of Pittsburgh.  Li Tan, Digital Signal Processing Fundamentals and Applications, DeVry University Decatur, Georgia  Signal processing is the analysis, interpretation, and manipulation of signals like: sound, images and sensor data etc…  For example biological data such as electrocardiograms, control system signals, telecommunication transmission signals such as radio signals, and many others.  When a signal is transmitted from one point to another there is every possibility of contamination /deformation of the signal by external noise. So to retrieve the original signal at the receiver suitable filters are to be used. i.e. the signal is processed to obtain the pure signal. 1. Analog signal processing For signals that have not been digitized, as in classical radio, telephone, radar, and television systems. This involves electronic circuits such as passive filters, active filters, additive mixers, integrators and delay lines. 2. Digital signal processing For signals that have been digitized, processing is done by general-purpose computers or by digital circuits such as field-programmable gate arrays (FPGA) or specialized digital signal processors (DSP chips).  The concept of DSP is illustrated by the simplified block diagram in the above figure, which consists of: an analog filter, an analog-to-digital conversion (ADC) unit, a digital signal (DS) processor, a digital-to-analog conversion (DAC) unit, and a reconstruction filter.  The digital signal processor may be a large programmable digital computer or a small microprocessor programmed to perform the desired operations on the input signal.  It may also be a hardware digital processor. Programmable machines provide the flexibility to change the signal operations through a change in the software.  In applications where the digital output from the digital signal processor is to be given to the user in analog form, such as in speech communication, we must add a digital to analog converter. In some other applications there is no need for the digital to analog converter.  Accuracy: The analog circuits are prone to temperature and external effects, but the digital circuits have no such problems.  Flexibility: Reconfiguration of analog circuits is very complex whereas the digital circuits can be reconfigured easily by changing the program coefficients.  In some cases a digital implementation of signal processing system is cheaper than its analog counterpart.  Digital signals can be easily stored on any magnetic media or optical media are using semiconductor chips.  Easy operation: Even complex mathematical operations can be performed easily using computers, which is not the case with analog processing.  Multiplexing: Digital signal processing provides the way for Integrated service digital network where digitized signals can be multiplexed with other digital data and transmitted through the same channel. There are also certain limitations in digital signal processing (DSP) :  Bandwidth restrictions, when the analog signals have a wide bandwidth, then high speed ADC are required.  Speed limitations  The DSP systems are expensive for small applications  An analog system is constructed using active, passive components like resistors, capacitors and op amps etc.. A digital system constitutes adder, multiplier and delay elements.  Ananalog system is denoted by a differential equation. A digital system is denoted by a difference equation.  Laplace transform is used for the analysis of analog systems. Z-transforms are used for the analysis of digital systems. … Alexa Robotics Amazon Shop Smart Mirror … Application Applications … Noise Filtering Voice Recognition Text to Speech Image Filtering Image Recognition … Related Algorithm Cosine IIR FIR FFT DSP Basic Transform Algorithm Algorithm Algorithm Algorithm Algorithm DSP Basic Algorithms  One or more of these algorithms are used in almost every signal processing application  FIR Filters and IIR Filters: are used to remove unwanted noise from signals being processed.  Convolution Algorithms: are used for looking for similarities in signals.  Discrete Fourier Transforms: are used for representing signals in formats that are easier to process.  Discrete Cosine Transforms: are used in image processing applications.