Edward Silva

Introduction to estimation theory with emphasis on the Kalman filter. Topics include random processes, state-space models, optimal linear filtering, extended Kalman filter, and applications to navigation and tracking.

State-space methods for analysis and design of control systems. Topics include state-space representations, controllability, observability, state feedback, observer design, and introduction to optimal control.

Theory and application of digital signal processing. Topics include discrete-time signals and systems, z-transforms, DFT/FFT, digital filter design (FIR and IIR), and multirate signal processing.

Designed, fabricated, and soldered a printed circuit board (PCB), applying layout best practices and real-world manufacturing constraints from concept to implementation.

Computational techniques for solving electrical engineering problems. Topics include numerical methods, MATLAB programming, signal analysis, and system simulation.

Introduction to electromagnetic field theory. Topics include electrostatics, magnetostatics, Maxwell's equations, plane waves, and transmission lines.

Introduction to semiconductor devices and electronic circuits. Topics include diodes, bipolar junction transistors, field-effect transistors, operational amplifiers, and frequency response.

Introduction to embedded microcontroller systems including hardware and software. Topics include timers, interrupts, analog-to-digital conversion, pulse-width modulation, and serial communication.

Hands-on laboratory exploring system design concepts through team-based projects integrating hardware and software components.

Introduction to random variables, random processes, and noise in linear systems. Applications to communication systems including matched filters, signal-to-noise ratio, and bit error rate.

Introduction to continuous-time and discrete-time signals and systems. Topics include convolution, Fourier series, Fourier transforms, sampling, and the z-transform.

An introduction to linear feedback control systems. Modeling of linear systems using transfer functions and state-space representations. Analysis and design using root-locus and frequency-response methods.