Image analysis is an important component of neuroscience research. The ICT infrastructure and technical knowledge needed to perform (large scale) neuroimaging studies, however, is...
In this paper we use the cumulative distribution of a random variable to define the information content in it and use it to develop a novel measure of information that parallels S...
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Compressive Sensing (CS) is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compres...
Ali Cafer Gurbuz, James H. McClellan, Volkan Cevhe...
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...