Micro-Blog
March 11, 2019
The team met to reestablish goals for the project and reevaluate the timeline of goals.
March 7, 2019
The group successfully classified AM and FM signals (with over 85% accuracy) using their programs and their databases. They started creating a database of BPSK and QPSK signals to classify next.
March 5, 2019
The team successfully finished creating a databse of AM and FM signals to be used as training and testing data for their deep learning programs. The database was created by writing and executing a simple MATLAB script. The script can generate a user-determined number of signals, and save each plot of the signal automatically. The script adds in white Gaussian noise (with a SNR of 10) to simulate the real world.
February 21, 2019
The team met with Dr. Yao to show them their improved programs. During this session, the team and Dr. Yao discussed how they were to move forward. First, the team is to be able to identify and classify 2 different signals: AM and FM. Then, the team would identify and classify between BPSK and QPSK signals. All the signals were to be generated with MATLAB. After these signals are able to be identified with over 75% accuracy, the team would then use hardware to produce signals instead of MATLAB.
January 29, 2019
The group met with Dr. Yao to show him their current program. The current program classifies images according to two classes: shirt or shoe. Dr. Yao has assigned each group member to improve upon the program by classifying three classes. Each team member will be using different classes from each other.
December 5, 2018
The group met to prepare for the final presentation and finalize the website. They also continued work on creating data sets for identification using both Tensor Flow and Matlab.
December 2, 2018
The group met to work on 2 TG deliverables that are due 12/7/18. They also discussed the research they have been conducting on deep learning, and where to move forward from there.
November 28, 2018
The group met to prepare for finals season and presentation and to come up with a winter break timeline.
November 14, 2018
The group has done research on papers relating to the topic of communications deep learning projects, and analyzed papers from our advisor on previous similar projects.
November 8, 2018
The group met with Dr. Yao to show which tutorials they have been working on, and discussed how we can use the tutorials to write our own program for advanced wireless communications.
October 26, 2018
The group worked on analyzing and creating their risk and change assessment for TG and their project.
October 24, 2018
The group met with their advisor to give plans and talk about the progress of utilizing Tensorflow for analysis and tutorials
October 17, 2018
The group met to finish the TG deliverables and they worked on creating a plan and timeline for the project outcomes.
October 14, 2018
The group worked on the latest TG Deliverables (Scope Statement and Project Presentation). They planned to finish these items when they meet on this
Wednesday to work on their project
October 8, 2018
The group met in ABS to discuss their project further.
October 4, 2018
The group met with Dr. Yao to discuss the progress they have made so far, and how to proceed.
October 2, 2018
The group continues to work on TensorFlow tutorials.
September 24, 2018
Each group member started doing TensorFlow tutorials for image and text recognition.
September 20, 2018
The group attended the Shop and General Safety Orientation for Senior Design Students.
September 13, 2018
Each group member downloaded TensorFlow for Python and experimented with it.
September 11, 2018
The group had to choose which programming language they wanted to use for this project. Their main choices were MATLAB and Python. After discussing, the group decided that they wanted to move forward using Python.
September 6, 2018
The group met with Dr. Yao to discuss where to begin with this project. After the meeting, the group came up with a basic plan to approach and complete the project.
August 30, 2018
Group chose their project. After talking to various advisors, the group chose the Deep Learning for Communication Systems Identification project. Their advisor is Dr. Yao. The group discussed the gist of this project with Dr. Yao.