Course Description: This course covers continuous time signal models, convolution, and superposition integral and impulse response. Students also study Fourier series and periodic signals, Parseval's theorem, energy spectral density, Fourier transform and filters, discrete time signals, difference equations, discrete Fourier transform, and discrete convolution.

Course Overview: Signals is an introductory course that develops mathematical techniques for modeling continuous and discrete signals and linear systems. Analog and digital signal processing theory is taught simultaneously to emphasize the power of these mathematical abstractions. Classroom lectures are supplemented by computer simulations and Java applets that reinforce significant concepts. Topics covered in this course include basic linear system theory, time domain methods such as convolution, frequency domain methods such as the Fourier transform, the Z-transform, and filter design and implementation. This is a four credit hour lecture course that includes three hours of lecture and one credit hour of recitation.

Course Learning Objectives (CLO): Please refer to the common program outcomes for the College to understand the PO designations below.

1. Develop the ability to decompose complex engineering problems involving signals and linear systems into smaller conceptually simpler modules that can be analyzed and optimized (POs: A,C,E).
   
   
2. Design, simulate and optimize systems using Matlab (POs A, C, K).
   
   
3. Identify various types of signals and systems, and and perform routine operations in both the time and frequency domains (PO A).
   
   
4. Understand, visualize and manipulate various frequency domain representations (jw, s and z domains) of signals (PO A, E).

Course Topics: Refer to the CLOs above to understand how these topics relate to our stated program outcomes.

1. Signal and system classifications, properties and signal operations (CLO 2).
   
   
2. Continuous-time and discrete.time convolution and correlation (CLO 1, 2).
   
   
3. Fourier Series, Parseval's theorem, line spectra and power spectrum (CLO 1).
   
   
4. Fourier Transforms, Parseval's theorem, system frequency response. (CLO 1).
   
   
5. Filters, Bode plots and filtering (CLO 1, 3).
   
   
6. Z-plane plots and relationship to magnitude frequency response (CLO 1, 4),