Vector quantization (VQ) is an elementary technique for image compression. However, searching for the nearest codeword in a codebook is time-consuming. The existing schemes focus o...
We consider the problem of estimating a deterministic sparse vector x0 from underdetermined measurements Ax0 +w, where w represents white Gaussian noise and A is a given determinis...
We address the possibility of overloaded vector precoding in single user MIMO channels, i.e. the number of data streams is larger than the minimum of the number of antennas at tran...
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
Data compression is one way to alleviate the 1/0bottleneck problem faced by I/O-intensive applications such as databases. However, this approach is not widely used because of the ...