Distributed data clustering in sensor networks is receiving increasing attention with the development of network technology. A variety of algorithms for distributed data clustering have been proposed recently. However, most of these algorithms have trouble with either non-Gaussian shaped data clustering or model order selection problem.
This paper proposes a novel algorithm to determine the optimal orientation of sensing axes of redundant inertial sensors such as accelerometers and gyroscopes (gyros) for increasing the sensing accuracy. In this paper, we have proposed a novel iterative algorithm to find the optimal sensor configuration.
In this paper, we study the problem of compressed sensing using binary measurement matrices and ℓ1 -norm minimization (basis pursuit) as the recovery algorithm. We derive new upper and lower bounds on the number of measurements to achieve robust sparse recovery with binary matrices.
As a reminder, most of the SPS publications have eliminated month-based issues and moved to a volume-only, continuous pagination model. This allows for rapid dissemination of content for our journals and now, articles are posted to their respective journals on IEEEXplore® nearly every day!
The existence of gender imbalance in STEM fields continues to this day. UNESCO, in 2015, reported worldwide under-representation of women in STEM fields with only 30% women researchers in various fields. The key reasons of this disparity are lack of encouragement, guidance and resources.
The Member Election Subcommittee of the SLTC is announcing the results of the elections for members filling the 2020-2022 term. In this year's election, we had 17 openings in 9 areas that took into account retirements and recent ICASSP trends.
Dear Speech and Language Processing Community,
Happy new year! I hope that you all have had a successful conclusion to 2019 and that 2020 is an even brighter year. Indeed, our community is vibrant and growing: as we are in the middle of the ICASSP review process as I am writing this, I can report that the papers submitted to SLTC areas (encompassing Speech Processing and Human Language Technologies) grew by over 25% from the previous ICASSP.