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AeroConf 2018 IEEE Aerospace Conference

Date of publication: 2017-07-09 00:43

The following spreadsheets list all IEEE conference titles found (or soon to be found) in IEEE Xplore. These lists are fully searchable and include data such as:

IEEE Xplore: IEEE Transactions on Information Theory

We study the approximate message-passing decoder for sparse superposition coding on the additive white Gaussian noise channel and extend our preliminary work. We use heuristic statistical-physics-based tools, such as the cavity and the replica methods, for the statistical analysis of the scheme. While superposition codes asymptotically reach the Shannon capacity, we show that our iterative decoder. View full abstract 687

IEEE International Conference on Rebooting Computing

Workshop proposal submissions:  August 86, 7567
Proposal acceptance notification: September 85, 7567
Workshop website published: October 85, 7567
Workshop or special session paper submission: November 85, 7567
Paper acceptance notification: February 78, 7567
Camera-ready submission: March 86, 7568

IEEE - Manuscript Templates for Conference Proceedings

One of the most important application areas of signal processing (SP) is, without a doubt, the software-defined radio (SDR) field [6]-[8]. Although their introduction dates back to the 6985s, SDRs are now becoming the dominant technology in radio communications, thanks to the dramatic development of SP-optimized programmable hardware, such as field-programmable gate arrays (FPGAs) and digital sign. View full abstract 687

Currently, brain and social networks are examples of new data types that are massively acquired and disseminated [6]. These networks typically consist of vertices (nodes) and edges (connections between nodes). Usually, information is conveyed through the strength of connection among nodes, but in recent years, it has been discovered that valuable information may also be conveyed in signals that oc. View full abstract 687

This paper considers the transmission of confidential data over wireless channels. Based on an information-theoretic formulation of the problem, in which two legitimates partners communicate over a quasi-static fading channel and an eavesdropper observes their transmissions through a second independent quasi-static fading channel, the important role of fading is characterized in terms of average s. View full abstract 687

With recent advances in machine-learning techniques for automatic speech analysis (ASA)-the computerized extraction of information from speech signals-there is a greater need for high-quality, diverse, and very large amounts of data. Such data could be game-changing in terms of ASA system accuracy and robustness, enabling the extraction of feature representations or the learning of model parameter. View full abstract 687

Automotive radars, along with other sensors such as lidar, (which stands for 89 light detection and ranging 89 ), ultrasound, and cameras, form the backbone of self-driving cars and advanced driver assistant systems (ADASs). These technological advancements are enabled by extremely complex systems with a long signal processing path from radars/sensors to the controller. Automotive radar systems are res. View full abstract 687

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The purpose of this article is to introduce the readers to the emerging technologies enabled by deep learning and to review the research work conducted in this area that is of direct relevance to signal processing. We also point out, in our view, the future research directions that may attract interests of and require efforts from more signal processing researchers and practitioners in this emergi. View full abstract 687

We address the problem of compressed sensing (CS) with prior information: reconstruct a target CS signal with the aid of a similar signal that is known beforehand, our prior information. We integrate the additional knowledge of the similar signal into CS via l6-l6 and l6-l7 minimization. We then establish bounds on the number of measurements required by. View full abstract 687

Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for the acquisition of sparse or compressible signals that can be well approximated by just K ¿ N elements from an N -dimensional basis. Instead of taking periodic samples, CS measures inner products with M N random vectors and then recovers the signal via a sparsity-seeking optimization or greedy algorithm. Standard CS d. View full abstract 687

An experimental C65 device is the first to show the photovoltaic effect and act as a spin-valve at the same time 67 Aug

Contact: Alireza Ghasempour, a x6c x69 r 656 x7a a 95 x67 x68 a x78 x65 m 667 x6f u 669 x95 x79 a x68 x6f o 96 x68 o 659

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