cosc 4242 signals and systems introduction. motivation modeling, characterization, design and...
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Motivation
• Modeling, characterization, design and analysis of natural and man-made systems
• General approaches -> based upon theoretical and mathematical techniques
• Tools based upon the description and analysis of systems using differential and difference equations
• Time versus frequency domain representations – Fourier techniques
Applications
• Communications – AM, FM, FSK, PSK, communication channels
• Physical systems modeling and control- seismology, mechanics, chemical process control, aerospace, motor control, thermodynamics, fluid dynamics
• Radio-astronomy, geophysics• Optics and acoustics
Applications
• Biomedical engineering
• Electronics, circuit design
• Neural networks, adaptive systems
• Computer vision, graphics, image and speech processing
• Time series analysis, economic forecasting, stock trends
Analogue versus Digital Signal Processing
• Main distinction is continuous versus discrete• Analogue signal processing – many real world
systems are analogue, control and processing in analogue domain with analogue circuits (RLC, diodes, amps ....) or with mechanical or other physical elements
• DSP – digital circuits/program (adders, multipliers and memory)
Why Analogue?
• Natural solution of differential equations• Strong arsenal of techniques for design of
analogue filters etc.• No need for approximation, sampling, numerical
computations• Real time, less complex circuitry • BUT component values drift, imprecise tolerance,
age and temperature variations, difficult with very small and very large components, non ideal realizations
Why Digital?
• Flexible, same hardware can perform multiple functions, upgrade and update possible
• Repeatability and precision, higher-order systems • Natural for interface with high level supervisory
control software • BUT takes time to compute and circuit complexity
is high (especially with general purpose hardware)
• Most systems are ‘mixed’ combining some analogue and some digital components– digital hardware is so cheap it almost always an option
despite increased circuit complexity for digital implementation
• Digital techniques for data acquisition, signal filtering, detection, processing and automatic control are sometimes approximations of analogue solutions and are sometimes fully ‘digital’ designs