School of Engineering Department of Electronic and Computer Engineering 131 Department of Electronic and Computer Engineering Federated Learning over Wireless Networks Supervisor: CAO Xuanyu / ECE Student: LIN Yiqiao / CPEG Course: UROP1100, Spring UROP2100, Summer Traditionally, federated learning aims to train a single global model with several local clients and a server working collaboratively without raw data exchanges. However, this mechanism only develops a single common model for all users, not customized to each client’s data. Previously, we proposed an algorithm named ETCPer-FedAvg, which can greatly reduce the communication overhead while finding the meta-model. This report continues the progress from previous term and gives a more detailed analysis of the proposed algorithm. We evaluate how the performance of the algorithm is affected by the closeness of underlying distribution of user data, triggering threshold and compression operator in nonconvex smooth case. Projects in Audio Signal Processing - Hearing Loss Simulation and Compensation with Wavelet Transform Supervisor: CHAU Kevin / ECE Student: CHAN Kelvin Cheuk Kwan / SENG MOK Ching Hei / SENG Course: UROP1000, Summer UROP1000, Summer Hearing compensation is implemented in hearing aids, with most of them using Fourier transform. However, wavelet transform with multiresolution analysis provides greater balance between the time-frequency resolution for the modelling of real-world sounds. Moreover, wavelet transform provides a faster runtime than Fourier transform. To understand more about hearing and hearing loss, hearing loss simulation and compensation were first done in the frequency domain. After that, attempts were made to migrate the simulation and compensation function from the frequency to the wavelet domain. A proposition for a wavelet-based model for hearing loss simulation and compensation, as well as its limitations, were discussed in the paper.