A new dictionary selection approach for sparse coding, called parametric dictionary design, has recently been introduced. The aim is to choose a dictionary from a class of admissi...
Mehrdad Yaghoobi, Laurent Daudet, Michael E. Davie...
In this paper we propose two fast Total Variation (TV) based algorithms for image restoration by utilizing variational posterior distribution approximation. The unknown image and ...
Bruno Amizic, S. Derin Babacan, K. Michael Ng, Raf...
Applications to evaluate Internet quality-of-service and increase network security are essential to maintaining reliability and high performance in computer networks. These applic...
—This paper provides a framework for designing space-time codes to take advantage of a small number of feedback bits from the receiver. The new codes are based on circulant matri...
Compressive-sensing cameras are an important new class of sensors that have different design constraints than standard cameras. Surprisingly, little work has explored the relation...
This paper presents the results of formant analysis using a newly developed formant contour model. We model formant contours with a linear combination of formant target values and...
Sparse signal recovery algorithms utilizing multiple measurement vectors (MMVs) are known to have better performance compared to the single measurement vector case. However, curre...
The achievable rate of digital communications systems can strongly depend on the analog-to-digital conversion at the receiver. It is hence important to adjust the gain control at ...
This paper proposes a guaranteed robust bounded-error distributed estimation algorithm. It may be employed to perform parameter estimation from data collected in a network of wire...
We study the convergence behavior of the Active Mask (AM) framework, originally designed for segmenting punctate image patterns. AM combines the flexibility of traditional active...
Doru-Cristian Balcan, Gowri Srinivasa, Matthew C. ...