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The Latest News, Articles, and Events in Signal Processing
July 2-5, 2019
Location: Cannes, France
April 8-11, 2019
Location: Venice, Italy
Title: Speech research/machine learning internship @Alibaba
Time: Summer/Fall, 2018
Job location: Seattle / San Francisco / Beijing
Link: https://sites.google.com/site/gangliuresearch/jobs
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The IEEE Signal Processing Society continues to track emerging technical areas. As a result, the Society has decided to create two new SPS Technical Interest Profile (TIP) Code categories in the fields of Data Science and Autonomous Systems to keep pace with the expanding technical disciplines.
PhD Studentships in Signal Processing Techniques
Programe of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil
Applications are invited for PhD studentships in signal processing techniques. These studentships are funded by the CNPq/CAPES research councils in Brazil. The topic of the project is open in the broad area of signal processing techniques. Potential topics include:
Patent no. 9,959,455 presents a system for facial recognition comprising at least one processor; at least one input operatively connected to the at least one processor; a database configured to store three-dimensional facial image data comprising facial feature coordinates in a predetermined common plane;
By bringing research into the curriculum, this article explores new opportunities to refresh some classic signal processing courses. Since 2015, we in the Electrical and Electronic Engineering (EEE) Department of Imperial College London, United Kingdom, have explored the extent to which the level of student engagement and learning can be enhanced by inviting the students to perform signal processing exercises on their own physiological data.
Speech coding is a field in which compression paradigms have not changed in the last 30 years. Speech signals are most commonly encoded with compression methods that have roots in linear predictive theory dating back to the early 1940s.
Technologies that at first seem like magic soon become so commonplace that we no longer even think about how amazing they are – or wonder how they operate. Our digital home assistants – Amazon’s Alexa, Google Home and their emerging rivals – have been with us long enough that we take for granted they can understand our unique voices, commands and questions, even with other noise occurring around them.
IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC. Visit the SPS Job Submission Form.
he Signal Processing Society (SPS) has 12 Technical Committees and 3 Special Interest Groups (SIGs) that support a broad selection of signal processing-related activities defined by the scope of the Society.
The IEEE Signal Processing Society welcomes proposals from prospective organizers of 2018-2019 winter schools under the S3P (Seasonal Schools in Signal Processing) Program. S3P seasonal schools are typically either summer schools or winter schools, and are geared towards providing graduate students, early stage researchers, and practitioners with background on selected topics in signal processing.
Starting in 2017, the Women in Signal Processing (WISP) Subcommittee became a standing committee of the Membership Board, rather than a subcommittee of the Member Services Committee. This means that the WISP chair now holds a seat on the Membership Board.
As the size and speed of many conventional electronics technologies begin reaching their practical limits, a growing number of researchers is turning their attention to photonics and related optical-based approaches to continue the push toward smaller, faster, cheaper, and more innovative computer and communication devices.
By bringing research into the curriculum, this article explores new opportunities to refresh some classic signal processing courses. Since 2015, we in the Electrical and Electronic Engineering (EEE) Department of Imperial College London, United Kingdom, have explored the extent to which the level of student engagement and learning can be enhanced by inviting the students to perform signal processing exercises on their own physiological data.
Processing, storing, and communicating information that originates as an analog signal involves converting this information to bits. This conversion can be described by the combined effect of sampling and quantization, as shown in Figure 1. The digital representation is achieved by first sampling the analog signal to represent it by a set of discretetime samples and then quantizing these samples to a finite number of bits.
Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive sensing (CS)-enabled approaches.
With the proliferation of Internet of Things (IoT) applications, billions of household appliances, phones, smart devices, security systems, environment sensors, vehicles, buildings, and other radio-connected devices will transmit data and communicate with each other or people, and it will be possible to constantly measure and track virtually everything.
Discrete-time rational transfer functions are often converted to parallel second-order sections due to better numerical performance compared to direct form infinite impulse response (IIR) implementations. This is usually done by performing partial fraction expansion over the original transfer function.
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- Join NASA’s Dr. Jacqueline Le Moigne for this interactive webinar as she shares her journey through the realms of signal processing, computer vision, and related technologies, including her pivotal roles at NASA. https://x.com/IEEEsps/status/1782468413551423536
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