Undergraduate Student Demos & Presentations

In this project we investigated a relatively novel approach to signal processing, using Topological Data Analysis (TDA) methods. We first transfer the signal to a Point Cloud structure, using Sliding Window Embedding, and we study global features of this cloud. Then, by constructing a sequence of Simplicial Complexes with the Alpha Complex structure, we extract information of qualitative topological properties of the point cloud, such as holes, air pockets, and their higher-order analogues. We show that a careful selection of the parameters controlling the transformation of the signal to a point cloud allows for the extraction of significant information about the signal. Furthermore, it could lead to outperform classical Fourier analysis in the study of the difference between periodic and quasi-periodic signals. Based on these insights, we created several scoring methods for identifying powerful topological features and applied them to develop a technique for alarm sound detection in noisy environments that outperforms the state-of-the-art.

2nd award winner at the Yehoraz Kasher Annual Project Contest 2021 at the Faculty of Electrical and Computer Engineering, Technion

Click here for the poster