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Credit: 1 course
unit
Required course (Junior year)
Catalog Description:
Properties of signals and systems and examples of biological and
biomedical signals and systems; linear, time invariant systems; Fourier analysis
of signals and systems with applications to biomedical signals such as
ECG and EEG; frequency analysis of first and second order systems;
frequency response of systems characterized by linear
constant-coefficient differential equations; introduction to ditigal and
analog filtering, sampling and sampling theorem and aliasing.
Prerequisites: BE 210,
MATH 241
Textbook(s) and/or Other Required Materials:
Lathi, Signal Processing and Linear Systems (Oxford)
Recommended: Matlab student edition
Course Objectives:
This course is a requirement for bioengineering majors. The goal
of the course is to introduce students to the analysis of continuous and
sampled signals using classical techniques including Laplace, Fourier and
Z transforms, and the relevance of this theory to biomedical engineering.
The course includes extensive computer assignments using Maple and Matlab
for the analysis of linear systems and design of digital filters.
Topics Covered:
·
Introduction
to signals and systems
·
Introduction
to Matlab and Maple
·
solution
of ODEs
·
classical
approach (complementary function* and particular integral solution*)
·
systems
approach (zero state and zero input responses)
·
response
of thermistor to temperature pulse in Swan-Ganz catheter (HW2)
·
Impulse
response and convolution; graphical solution to convolution problems
·
Fourier
series and frequency content of signals
·
Fourier
transform and windows
·
Sampling;
sampling theorem; reconstruction; DFT
·
Laplace
transform, inverse Laplace transform,
use of transform to solve differential equations
·
Analysis
of CT systems; poles, zeros, frequency response; Bode plots
·
Analog
Butterworth filter; frequency scaling, lowpass to highpass and bandpass
transformation
·
Introduction
to digital filtering
·
Bioengineering
applications:
·
modeling
dynamic properties of transducers
·
linearization
of thermistor
·
step
response of a thermistor
·
compartmental
model
·
Fourier
analysis of ECG signal
·
identification
of aliasing artifacts
·
design of
analog antialiasing filter
·
design of
digital IIR and FIR filters for ECG
Class/Laboratory Schedule:
Lecture: 3 hrs/week
Recitation (optional): 1 hr/week
Contribution
towards Professional Component:
100% Engineering science
Contribution
towards Program Outcomes:
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Multidisciplinary
Ability
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High
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Problem Solving
Approach
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High
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Problem Solving
Methods
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Med.
|
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Experimentation
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Low
|
|
Design
|
Low
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Professional
Orientation
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Low
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Person(s) Preparing
Description and Date:
K. R. Foster
July 2007
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