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Election Regional Directors-at-Large and Members-at-Large

It is my pleasure to announce that the IEEE Signal Processing Society (SPS) annual election will commence on 15 August, and your vote is more important than ever! This year, all eligible SPS Members will vote for the Regional Directors-at-Large for Regions 1-6 and 8 (term 1 January 2023 through 31 December 2024), and Members-at-Large (term 1 January 2023 through 31 December 2025) of the IEEE Signal Processing Society Board of Governors (BoG).

SPS Webinar: 9 November 2022, presented by Dr. DeLiang Wang

As the most widely-used spatial filtering approach for multi-channel signal separation, beamforming extracts the target signal arriving from a specific direction. We present an emerging approach based on multi-channel complex spectral mapping, which trains a deep neural network (DNN) to directly estimate the real and imaginary spectrograms of the target signal from those of the multi-channel noisy mixture. 

Memories From a Historic, Hybrid, Distributed ICASSP

This past May marked the beginning of our return to face-to-face events after almost three years of pandemic-forced virtual-only interactions. The first attempt was the 2022 ICASSP! Planning for large international events in the era of postpandemic uncertainty is not an easy undertaking. Of course, signal processing is all about dealing with uncertainty—and who would be better at planning than IEEE Signal Processing Society (SPS) people?

A Trick for Designing Composite Filters With Sharp Transition Bands and Highly Suppressed Stopbands

Designing a perfect filter (i.e., flat passband, sharp transition band, and highly suppressed stopband) is always the goal of digital signal processing practitioners. This goal is reachable if we make no consideration of implementation complexity. In other words, the challenge of designing a high-performance filter is to leverage the distortion tradeoff in the passband, transition band, and stopband. 

Proper Definitions of Dirichlet Conditions and Convergence of Fourier Representations

Fourier theory is the backbone of signal processing (SP) and communication engineering. It has been widely used in almost all branches of science and engineering in numerous applications since its inception. However, Fourier representations such as Fourier series (FS) and Fourier transform (FT) may not exist for some signals that fail to fulfill a predefined set of Dirichlet conditions (DCs).