Discrete-time signal and system representations. Linear time invariant systems, impulse responses, convolution. Frequency-domain analysis of discrete-time signals and systems: Fourier series, Fourier Transforms, frequency responses, filtering. Discrete-time processing of continuous-time signals. Z Transforms for systems analysis: transfer functions, stability. Design of FIR and IIR filters. Introduction to random processes and statistical noise models. Applications in digital communications and signal processing systems.

Analysis of circuit response to sinusoidal excitation; phasor analysis, impedance, admittance, power, frequency response, transfer functions, Bode plots, filters. Linear analysis of nonlinear circuits; DC biasing of 3 terminal devices, small signal analysis, single device amplifiers, small signal gain and frequency response.

This course will introduce students to the notion of waves through the context of transmission lines and electromagnetic propagation in simple unbounded media, and also introduce the theory of electromagnetism and electromagnetic fields and waves and their interaction with simple media and structures. The course includes the following topics: Transmission lines modeled as distributed circuits; introduction to one dimensional waves and the wave equation; wave velocity. Time-harmonic representation of waves and Helmholtz equation; wavelength and wavenumber.

An introduction to computer architecture and hardware design. Topics include: computer abstractions and technology, performance evaluation, instruction set architectures, computer arithmetic, pipelining, memory systems, and interfacing. Laboratory assignments will include the use of hardware description languages, machine languages and assembly languages, and hardware emulation using FPGA boards. State-of-the-art computer simulation tools are used as part of the course.

Overview of the electrical and computer engineering field, including introduction to various subdisciplines and the corresponding upper-level ECE courses.

Properties of complex numbers. Rectangular, exponential, and graphical representations of complex numbers. Euler's identity and translating between representations. Basic and advanced operations with complex numbers, such as adding, subtracting, multiplying, and dividing, as well as exp(z), ln(z), a^z, and z^a. Applying knowledge of complex numbers to linear algebra and differential equations using MATLAB.

This class covers the fundamental of the nanoelectronics discipline ranging from nanophysics, to nano structures and nanodevices. It provides first an overview of the fundamental physical principles required for understanding the electronic properties of matter at the nanoscale. From the basic description of quantum dots, wires and wells, we will review the main electrical property differences between atoms, molecules and nanostructures including Carbon nanotubes and Nanoribbons.

Complex numbers. First-order differential equations. Matrices and systems of linear equations. Vector spaces and linear transformations. 2nd-order linear differential equations and the Laplace transform. Systems of differential equations.

Mathematical models for analog circuit elements such as resistors, capacitors, opamps and MOSFETs as switches. Basic circuit laws and network theorems applied to dc, transient, and steady-state response of first- and second-order circuits. Modeling circuit responses using differential equations Computer and laboratory projects. NOTE: Grades of C or better in MATH 132 and PHYSICS 152 are strongly recommended.

Mathematical models for analog circuit elements such as resistors, capacitors, opamps and MOSFETs as switches. Basic circuit laws and network theorems applied to dc, transient, and steady-state response of first- and second-order circuits. Modeling circuit responses using differential equations Computer and laboratory projects. NOTE: Grades of C or better in MATH 132 and PHYSICS 152 are strongly recommended.