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Uin Uout R Uin L C Uout
▶ passive networks are highly linear
Uin Uout 1/√LC
ω (=2πf )
over a very large dynamic range and large bandwidths
▶ analog signal-processing circuits
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction
ECS
Typical DSP applications
▶ communication systems
modulation/demodulation, channel equalization, echo cancellation
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction
ECS
Assessment
▶
2 hour exam, answer 3 questions from 5, worth 90% of final mark. One coursework worth 10% of final mark — this will be set at the end of week 5 and to be submitted 3 weeks later.
ECS
Digital signal processing
Analog/digital and digital/analog convertor, CPU, DSP, ASIC, FPGA. Advantages:
▶ noise is easy to control after initial quantization ▶ highly linear (within limited dynamic range) ▶ complex algorithms fit into a single chip ▶ flexibility, parameters can easily be varied in software ▶ digital processing is insensitive to component tolerances, aging,
▶ medical diagnostics
magnetic-resonance and ultrasonic imaging, computer tomography, ECG, EEG, MEG, AED, audiology
▶ engineering
control systems, features extraction for pattern recognition
easily manipulated building blocks
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction ECS
Analog electronics
Passive networks (resistors, capacitors, inductances, crystals, SAW filters), non-linear elements (diodes, ...), (roughly) linear operational amplifiers Advantages:
environmental conditions, electromagnetic interference But:
▶ discrete-time processing artifacts (aliasing) ▶ can require significantly more power (battery, cooling) ▶ digital clock and switching cause interference
ELEC 6099 — Signal Processing — Course Introduction
Professor Eric Rogers
School of Electronics and Computer Science University of Southampton etar@ Office: Building 1, Room 2041
accelerometer, antenna,etc.)
▶ electrical signal that controls a process
Continuous-time signals: voltage, current, temperature,speed,.... Discrete-time signals: daily minimum/maximum temperature,lap intervals in race,sampled continuous signals,...
sensor-data evaluation
▶ aviation
radar, radio navigation
▶ music
synthetic instruments, audio effects, noise reduction
▶ security
steganography, digital watermarking, biometric identification, surveillance systems, signal intelligence, electronic warfare
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction
ECS
Lecture and Tutorial Slots
▶ ▶ ▶
Tuesday 5 pm — 6 pm. Wednesday 11 am – noon. Thursday 11 am – noon.
▶ astronomy
VLBI, speckle interferometry
▶ consumer electronics
perceptual coding of audio and video on DVDs, speech synthesis, speech recognition
▶ experimental physics
0
t
require little or no power
▶ analog circuits cause little additional
Uin − Uout 1 = R L
∫
t
Uout d + C
−∞
dUout dt
interference
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction
▶
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction
ECS
Course Texts
The material in these notes is covered by a large number of texts. If you need a book to support the lectures then any of the following are suitable choices.
▶
▶
▶
Professor Eric Rogers ELEC 6099 — Signal Processing — Course Introduction
ECS
Signals
▶ flow of information ▶ measured quantity that varies with time (or position) ▶ electrical signal received from a transducer (microphone, thermometer,
Electronics(unlike optics) can only deal easily with time-dependent signals, therefore spatial signals, such as images, are typically first converted into a time signal with a scanning process (TV,fm , R. W. Schafer and J. R. Back, Discrete-time Digital Signal Processing, Prentice Hall Int 1999. A. V. Oppenheim , A. S. Willsky and S. H. Nawab, Signals and Systems, Prentice Hall Int 1996. P. Denbigh, System Analysis and Signal Processing, Addison-Wesley,1998. M. J. Roberts, Signals and Systems, McGraw Hill, 2003.
To do so, we also need
▶ methods to measure, characterise, model and simulate transmission
channels
▶ mathematical tools that split common channels and transformations into
