Amin Rahimi - Schoolwork - Classes

The following is a list of courses I've taken while at UCSD. Click on a title to read the course description.

 

Electrical Engineering courses:

Lower division:

Upper division, breadth:

Upper division, depth:

Math courses:

Lower division:

Upper division:

Physics courses:

Lower division:

 

Course Descriptions:

ELECTRICAL ENGINEERING COURSES:

8A-B. Introduction to Computer Science: Java
Basic UNIX. Basics of Java language. Classes, methods, and parameters. Modularity and abstraction. Documentation techniques. Testing and verification techniques. Inheritance. Event driven programming. Programming with AWT library or other similar library. Exception Handling.

ECE20A. Introduction to Electrical Engineering I
Areas of electrical engineering from Ohm's Law to semiconductor physics to engineering ethics are discussed, demonstrated, and experienced. Principles introudced in lectures are put to use as student lab teams build a working system. The first quarter emphasizes analog electronics.

ECE20B. Introduction to Electrical Engineering II
This continuation of ECE 20A emphasizes semiconductor devices and digital electronics. Lab teams complete their system as they learn engineering design methods. Students are prepared for processing toward their choice of an electrical engineering profession.

30. Introduction to Computer Engineering
The fundamentals of both the hardware and software in a computer system. Topics include: representation of information, computer organization and design, assembly and microprogramming, current technology in logic design.

ECE60A. Circuits and Systems I
Voltage-current relationships for circuit elements, Kirchoff's voltage and current laws, source transformations, loop and node analysis, initial conditions, the Laplace transform, inverse transforms, partial fraction expansions.

ECE60B. Circuits and Systems II
Solution of network equations using Laplace transforms; convolution integral; the concept of impedance; Thevenin's and Norton's theorems; transfer functions; poles and zeroes; two-port networks; steady state sinusoidal response; Bode plots.

ECE60L. Circuits and Systems Laboratory
In this course, students learn to model, simulate, and design practical circuits using idealized circuit models to account for the interactions among various parts of a circuit, the concept of feedback, etc. Topics include first and second order filters, operational amplifiers (linear amplifiers, active filters, differentiators, integrators, comparators, triggers, oscillators), and transistor circuits (amplifiers, digital circuits).

101. Linear Systems Fundamentals
Complex variables. Singularities and residues. Signal and system analysis in continuous and discrete time. Fourier series and transforms. Laplace and z-transforms. Linear Time Invariant Systems. Impulse response, frequency response, and transfer functions. Poles and zeros. Stability. Convolution. Sampling. Aliasing.

102. Introduction to Active Circuit Design
Nonlinear active circuits design. Nonlinear device models for diodes, bipolar and field-effect transistors. Linearization of device models and small signal equivalent circuits. Circuit designs will be simulated by computer and tested in the laboratory.

103. Fundamentals of Devices and Materials
Introduction to semiconductor materials and devices. Semiconductor crystal structure, energy bands, doping, carrier statistics, drift and diffusion. p-n junctions, metal-semiconductor junctions. Bipolar junction transistors: current flow, amplification, switching, non-ideal behavior. Metal-oxide-semiconductor structures, MOSFETs, device scaling.

107. Electromagnetism
Electrostatics and magnetostatics; electrodynamics; Maxwell’s equations; plane waves; skin effect. Electromagnetics of transmission lines: reflection and transmission at discontinuities, Smith chart, pulse propagation, dispersion. Rectangular waveguides. Dielectric and magnetic properties of materials. Electromagnetics of circuits.

108. Digital Circuits
Digital integrated electronic circuits for processing technologies. Analytical methods for static and dynamic characteristics. MOS field-effect transistors and bipolar junction transistors, circuits for logic gates, flip-flop, data paths, programmable logic arrays, memory elements.

109. Engineering Probability and Statistics
Axioms of probability, conditional probability, theorem of total probability, random variables, densities, expected values, characteristic functions, transformation of random variables, central limit theorem. Random number generation, engineering reliability, elements of estimation, random sampling, sampling distributions, tests for hypothesis.

118. Computer Interfacing
Interfacing computers and embedded controllers to the real world: busses, interrupts, DMA, memory mapping, concurrency, digital I/O, standards for serial and parallel communications, A/D, D/A, sensors, signal conditioning, video, and closed loop control. Students design and construct an interfacing project.

161A. Introduction to Digital Signal Processing
Review of discrete-time systems and signals, Discrete-Time Fourier Transform and its properties, the Fast Fourier Transform, Z-transforms, design of Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters, implementation of digital filters.

171A. Linear Control System Theory
Stability of continous- and discrete-time single-input/single-output linear time-invariant control systems emphasizing frequency domain methods. Transient and steady-state behavior. Stability analysis by root locus, Bode, Nyquist, and Nichols plots. Compensator design.

171B. Linear Control System Theory
Time-domain, state-variable formulation of the control problem for both discrete-time and continous-time linear systems. State-space realizations from transfer function system description. Internal and input-output stability, controllability/observability, minimal realizations, and pole-placement by full-state feedback.

172A. Introduction to Intelligent Systems: Robotics and Machine Intelligence
This course will introduce basic concepts in machine perception. Topics covered will include: edge detection, segmentation, texture analysis, image registration, and compression.

173. Theory and Applications of Neural Networks and Fuzzy Logic
Theory of fuzzy logic, reasoning and control; mathematical aspects of neural architectures for pattern classification, functional approximation, and adaptive estimation and control; theory of computer-assisted learning (supervised, unsupervised and hybrid); theory and practice of recurrent networks (stability, placement of equilibria); computer-aided design of fuzzy and neural systems, Bayes and minimax design.

174. Introduction to Linear and Nonlinear Optimization with Applications
The linear least squares problem, including constrained and unconstrained quadratic optimization and the relationship to the geometry of linear transformations. Introduction to nonlinear optimization. Applications to signal processing, system identification, robotics, and circuit design.

187. Introduction to Biomedical Imaging and Sensing
Image processing fundamentals: imaging theory, image processing, pattern recognition; digital radiography, computerized tomography, nuclear medicine imaging, nuclear magnetic resonance imaging, ultrasound imaging, microscopy imaging.

191. Engineering Group Design Project
Groups of students work to design, build, demonstrate, and document an engineering project. All students give weekly progress reports of their tasks and contribute a section to the final project report.

 

MATH COURSES:

21C. Calculus and Analytic Geometry for Science and Engineering
Vector geometry, vector functions and their derivatives. Partial differentiation. Maxima and minima. Double integration.

21D. Introduction to Differential Equations
Infinite series. Ordinary differential equations: exact, separable, and linear; constant coefficients, undetermined coefficients, variations of parameters. Series solutions. Systems, Laplace transforms, technique for engineering sciences. Computing symbolic and graphical solutions using Matlab.

20E. Vector Calculus
Change of variable in multiple integrals, Jacobian Line integrals, Green's theorem. Vector fields, gradient fields, divergence, curl. Spherical and cylindrical coordinates. Taylor series in several variables. Surface integrals, Stoke's theorem. Gauss' theorem and its applications. Conservative fields.

20F. Linear Algebra
Matrix algebra, solution of systems of linear equations by Gaussian elimination, determinants. Linear and affine subspaces, bases of Euclidean spaces. Eigenvalues and eigenvectors, quadratic forms, orthogonal matrices, diagonalization of symmetric matrices. Applications. Computing symbolic and graphical solutions using Matlab.

103A. Modern Applied Algebra
Abstract algebra with applications to computation. Set algebra and graph theory. Groups, rings and fields

109. Mathematical Reasoning
This course uses a variety of topics in mathematics to introduce the students to rigorous mathematical proof, emphasizing quantifiers, induction, negation, proof by contradiction, naive set theory, equivalence relations and epsilon-delta proofs.

120A. Elements of Complex Analysis
Complex numbers and functions. Analytic functions, harmonic functions, elementary conformal mappings. Complex integration. Power series. Cauchy's theorem. Cauchy's formula. Residue theorem.

130A. Ordinary Differential Equations
Linear and nonlinear systems of differential equations. Stability theory, perturbation theory. Applications and introduction to numerical solutions.

 

PHYSICS COURSES:

2A. Mechanics
A calculus-based science-engineering general physics course covering vectors, motion in one and two dimenstions, Netwon's first and second laws, work and energy, conservation of energy, linear momentum, collisions, rotational kinematics, rotational dynamcs, equilibrium of rigid bodies, oscillations, gravitation.

2B. Electricity and Magnetism
Continuation of Physics 2A covering charge and matter, the electric field, Gauss's law, electric potential, capacitors and dielectrics, current and resistance, electromotive force and circuits, the magnetic field, Ampere's law, Faraday's law, inductance, electromagnetic oscillations, gravitation.

2C. Fluids, Waves, Thermodynamics, and Optics
Continuation of Physics 2B covering fluid mechanics, waves in elastic media, sound waves, temperature, heat and the first law of thermodynamics, Maxwell's equations, electromagnetic waves, geometric optics, interference and diffraction.

2D. Relativity and Quantum Physics
A modern physics course covering atomic view of matter, electricity, and radiation, atomic models of Rutherford and Bohr, relativity, X-rays, wave and particle duality, matter waves, Schrodinger's equation, atomic view of solids, natural radioactivity.