We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...
Time information is critical for a variety of applications in distributed environments that facilitate pervasive computing and communication. This work describes and evaluates a no...
This paper presents a model for watermarking and some attacks on watermarks. Given the watermarked signal, the so-called Wiener attack performs minimum mean-squared error (MMSE) es...
Abstract--In multinode cooperative communications, simultaneous transmissions from two or more nodes are challenging due to its asynchronous nature. In addition, channel estimation...