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 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.

Student Outcomes (SO):

• SO C: An ability to creatively design a system, component or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
  
  
• SO D: An ability to function effectively on multi-disciplinary teams.
  
  
• SO G: An ability to communicate effectively in writing, speaking and making presentations.
  
  Course Topics: Refer to the SOs above to understand how these topics relate to our stated student outcomes.
  1. Signal and system classifications, properties and signal operations (SO C).
     
     
  2. Continuous-time and discrete.time convolution and correlation (SO C).
     
     
  3. Fourier Series, Parseval's theorem, line spectra and power spectrum (SO C).
     
     
  4. Fourier Transforms, Parseval's theorem, system frequency response. (SO C).
     
     
  5. Filters, Bode plots and filtering (SO C).
     
     
  6. Z-plane plots and relationship to magnitude frequency response (SO C),
     
     
  7. Signal detection and classification challenge (SO 2, 3).
     
     
  8. Team-based problem-solving in recitation (SO 2, 3).
     
     
  9. Writing assignments on contemporary topics in signal processing (SO 2, 3).