Computational Sensing: Spectroscopy
Catalog Data: 

Graduate Course Information


ECE 634 - Computational sensing: Spectroscopy

Credits: 3.00

Course Website:

UA Catalog Description:

Course Assessment:

Homework:  4 assignments

Project:  1 team project

Grading Policy:

Typically: 35% Homework,

                 35% Project,

                 30% Class participation and case studies

Course Summary:

Recent years have seen the growth of computational sensing—sensor system design that assumes full integration of computational processing into sensor operation. The result is sensor system with capabilities that are not possible with traditional methods. This course looks at this design mindset as it is applied to the sensing modality of spectroscopy.


Optical spectroscopy (spectroscopy utilizing wavelengths from UV through IR), is an important sensing modality for chemical/material detection and identification because the relevant wavelengths are those that directly interact with the electronic and molecular structure of matter—thereby providing important information about the constituents of a sample. There has been tremendous growth in this area, particularly for medical and security applications. Unfortunately, the nature of spectroscopic signatures (manifestly non-negative, strength variations of many orders of magnitude, etc.) make the problem of extracting information from the measured spectrum especially challenging, and requires a highly-integrated approach.


This course is designed to provide exactly such an integrated view of the topic at the advanced graduate level. The first half of the course covers spectroscopic fundamentals and traditional spectrometer designs, while the second half looks at how signal processing/communication concepts (eg. channel coding) can be integrated into the design process to produce computational spectrometers as well as how specific detection/estimation techniques can be incorporated into the system design or used post-measurement to extract information from the spectra.

There are no specific course pre-requisites, however, the course assumes a solid understanding of linear system theory (eg. ECE 501), random processes (eg. ECE 503), and introductory optics (eg. ECE 559) at the graduate level.


Course Topics: 

1.     Fundamentals of E&M / Optics review

2.     Electronics structure of matter

3.     Light-matter interaction

4.     Types of optical spectroscopy

5.     Traditional spectroscopic designs

6.     Computational sensing principles

7.     Design of computational spectrometers

8.     Spectroscopic detection and estimation techniques

Class/Laboratory Schedule: 

Lecture:  150 minutes/week

Prepared by: 
Micheal Gehm
Prepared Date: 
April 2013

University of Arizona College of Engineering