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Section: Publications & Resources
Publication: IEEE Signal Processing Magazine
This article reviews technologies and algorithms for decoding volitional movement intent using bioelectrical signals recorded from the human body. Such signals include electromyograms, electroencephalograms, electrocorticograms, intracortical recordings, and electroneurograms. After reviewing signal features commonly used for interpreting movement intent, this article describes traditional movement decoders based on Kalman filters (KFs) and machine learning (ML).
Section: Events
Publication: IEEE Signal Processing Magazine
White Paper Due: December 8, 2021
Publication Date: January 2023
CFP Document
The Signal Processing (SP) research group at the Universität Hamburg in Germany is hiring a Postdoc (E13/E14) "Machine Learning for Speech and Audio Processing".
Section: Events
Lecture Date: August 10, 2021 -- Virtual Lecture
Chapter: Hyderabad Chapter
Chapter Chair: Abhinav Kumar
Topic: Random Walk on a Tree for Stochastic Optimization and Learning
Section: Events
August 2-6, 2021
Location: Virtual Conference
Registration Deadline: August 1, 2021 till 5PM local time
Registration Link
Issue Date:
Section: Events
July, 2021-Postpone of the Workshop IEEE CAMSAP2021 and Approval of the Workshop IEEE SAM2022
by Xiangrong Wang and Wei Liu
Due to uncertainty generated by the pandemic, the Ninth IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2021) has been postponed to 2023.
As approved by the SAM TC, the Twelfth IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM2022) will be held at Trondheim, Norway, on 20-23 June 2022 (the dates are subject to change).
Section: Publications & Resources
Publication: IEEE Journal of Selected Topics in Signal Processing
This paper investigates an intelligent reflecting surface (IRS) assisted simultaneous wireless information and power transfer (SWIPT) system. Multiple IRSs deployed on unmanned aerial vehicles (UAVs) and ground building are considered in the proposed system for enhancing transmission of information and energy simultaneously. The optimization problem is formulated to maximize the average achievable rate over N time slots by jointly optimizing power splitting (PS) ratio, transmit beamforming, phase shifts and trajectories of UAVs.
Section: Publications & Resources
Publication: IEEE Journal of Selected Topics in Signal Processing
Edge networks offer a promising solution for satisfying the increasing energy and computation needs of user devices with new data intensive services. A mutil-access edge computing (MEC) system with collocated MEC servers and base-stations/access points (BS/AP) has the ability to support multiple users for both data computation and wireless charging. We propose an integrated solution for wireless charging with computation offloading to satisfy the largest feasible proportion of requested wireless charging while keeping the total energy consumption at the minimum, subject to the MEC-AP transmit power and latency constraints.
Section: Publications & Resources
Publication: IEEE Open Journal of Signal Processing
In the era of big data, profitable opportunities are becoming available for many applications. As the amount of data keeps increasing, machine learning becomes an attractive tool to analyze the information acquired. However, harnessing meaningful data remains a challenge. The machine learning tools employed in many applications apply all training data without taking into consideration how relevant are some of them. In this paper, we propose a data selection strategy for the training step of Neural Networks to obtain the most significant data information and improve algorithm performance during training.
Section: Publications & Resources
Publication: IEEE Open Journal of Signal Processing
The end users’ satisfactory Quality of Experience (QoE) is a fundamental criterion for networked video service providers such as video-on-demand providers (Netflix, YouTube, etc.), cloud gaming providers (Google Stadia, PlayStation Now, etc.) and videoconferencing providers (Zoom, Microsoft Teams, etc.). To know the QoE, providers today typically predict it from the Quality of Service (QoS) parameters or the client-side's actual QoE metrics measured at the current time-step.
