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The Latest News, Articles, and Events in Signal Processing
We generalize the 1-bit matrix completion problem to higher order tensors. Consider a rank-
In this paper, learning of tree-structured Gaussian graphical models from distributed data is addressed. In our model, samples are stored in a set of distributed machines where each machine has access to only a subset of features. A central machine is then responsible for learning the structure based on received messages from the other nodes.
Extracting information from a signal exhibiting damped resonances is a challenging task in many practical cases due to the presence of noise and high attenuation. The interpretation of the signal relies on a model whose order (i.e., the number of resonances) is in general unknown.
This study investigates various aspects of multi-speaker interference and its impact on speaker recognition. Single-channel multi-speaker speech signals (aka co-channel speech) comprise a significant portion of speech processing data. Examples of co-channel signals are recordings from multiple speakers in meetings, conversations, debates, etc.
Improving the modeling and processing of nonstationary signals remains an important yet challenging problem. In the past, the most effective approach for processing these signals has been statistical modeling.
Machine learning and related statistical signal processing are expected to endow sensor networks with adaptive machine intelligence and greatly facilitate the Internet of Things (IoT). As such, architectures embedding adaptive and learning algorithms on-chip are oft-ignored by system architects and design engineers, and present a new set of design trade-offs.
The Bio-Imaging and Signal Processing Technical Committee (BISP-TC) of the IEEE Signal Processing Society (SPS) promotes activities in the broad technical areas of computerized image and signal processing with a clear focus on applications in biology and medicine.
As part of the IEEE Signal Processing Society (SPS), the Speech and Language Technical Committee (SLTC) promotes research and development activities for technologies that are used to process speech and natural language.
5G technology, with its promises of self-driving vehicles and immersive virtual reality, will be a data-hungry generation of wireless communications.
In the era of big data, analysts usually explore various statistical models or machine-learning methods for observed data to facilitate scientific discoveries or gain predictive power. Whatever data and fitting procedures are employed, a crucial step is to select the most appropriate model or method from a set of candidates.
This month's special issue of Proceedings of the IEEE provides a state-of-the-art overview of the field of silicon photonics, which is making a significant impact on fiber-optic communications and spreading to new areas such as sensors and deep learning.
In the era of big data, analysts usually explore various statistical models or machine-learning methods for observed data to facilitate scientific discoveries or gain predictive power. Whatever data and fitting procedures are employed, a crucial step is to select the most appropriate model or method from a set of candidates.
The title of this editorial is borrowed from a popular children’s lullaby from the 1800s, which reads “Twinkle, twinkle, little star, how I wonder what you are!” It reminds me of the vast expanse of unexplored space (and science) that lie before us.
There have been three key revolutions in the way that research has become accessible: publishing, code, and data. The second and third revolutions are still taking place, particularly driven by the rise of machine-learning and artificial intelligence research in the last decade. When I started my research career in 1995, the World Wide Web was still in its infancy.
Manuscript Due: May 5, 2019
Publication Date: December 2019
CFP Document
Lecture Date: January 21, 2019
Chapter: Italy
Chapter Chair: Mauro Barni
Topic: Toward Autonomous Video Surveillance
The Department of Electrical and Computer Engineering (ECE) at the George Washington University (GWU) invites applications for a tenured/tenure-track faculty appointment starting as early as Fall 2019, in the area of signal and image processing (SIP). The appointment will be at the rank of Assistant or Associate Professor.
The Department of Electrical and Computer Engineering (ECE) at the George Washington University (GWU) invites applications for a tenured/tenure-track faculty appointment starting as early as Fall 2019, in the area of signal and image processing (SIP). The appointment will be at the rank of Assistant or Associate Professor.
At Crestron Electronics, Inc we build the technology that integrates technology.
Rensselaer – IBM Research Partnership
Rensselaer Polytechnic Institute (Troy, NY) is embarking on an ambitious expansion in Computational Sciences and Engineering research and education, with a focus on creating a research cluster in the area of Artificial Intelligence (AI) and Machine Learning (ML).
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